Archive Layout with Content
A variety of common markup showing how the theme styles them.
Header one
Header two
Header three
Header four
Header five
Header six
Blockquotes
Single line blockquote:
Quotes are cool.
Tables
| Entry | Item | |
|---|---|---|
| John Doe | 2016 | Description of the item in the list |
| Jane Doe | 2019 | Description of the item in the list |
| Doe Doe | 2022 | Description of the item in the list |
| Header1 | Header2 | Header3 |
|---|---|---|
| cell1 | cell2 | cell3 |
| cell4 | cell5 | cell6 |
| cell1 | cell2 | cell3 |
| cell4 | cell5 | cell6 |
| Foot1 | Foot2 | Foot3 |
Definition Lists
- Definition List Title
- Definition list division.
- Startup
- A startup company or startup is a company or temporary organization designed to search for a repeatable and scalable business model.
- #dowork
- Coined by Rob Dyrdek and his personal body guard Christopher “Big Black” Boykins, “Do Work” works as a self motivator, to motivating your friends.
- Do It Live
- I’ll let Bill O’Reilly explain this one.
Unordered Lists (Nested)
- List item one
- List item one
- List item one
- List item two
- List item three
- List item four
- List item two
- List item three
- List item four
- List item one
- List item two
- List item three
- List item four
Ordered List (Nested)
- List item one
- List item one
- List item one
- List item two
- List item three
- List item four
- List item two
- List item three
- List item four
- List item one
- List item two
- List item three
- List item four
Buttons
Make any link standout more when applying the .btn class.
Notices
Watch out! You can also add notices by appending {: .notice} to a paragraph.
HTML Tags
Address Tag
1 Infinite LoopCupertino, CA 95014
United States
Anchor Tag (aka. Link)
This is an example of a link.
Abbreviation Tag
The abbreviation CSS stands for “Cascading Style Sheets”.
Cite Tag
“Code is poetry.” —Automattic
Code Tag
You will learn later on in these tests that word-wrap: break-word; will be your best friend.
Strike Tag
This tag will let you strikeout text.
Emphasize Tag
The emphasize tag should italicize text.
Insert Tag
This tag should denote inserted text.
Keyboard Tag
This scarcely known tag emulates keyboard text, which is usually styled like the <code> tag.
Preformatted Tag
This tag styles large blocks of code.
.post-title {
margin: 0 0 5px;
font-weight: bold;
font-size: 38px;
line-height: 1.2;
and here's a line of some really, really, really, really long text, just to see how the PRE tag handles it and to find out how it overflows;
}
Quote Tag
Developers, developers, developers…
–Steve Ballmer
Strong Tag
This tag shows bold text.
Subscript Tag
Getting our science styling on with H2O, which should push the “2” down.
Superscript Tag
Still sticking with science and Isaac Newton’s E = MC2, which should lift the 2 up.
Variable Tag
This allows you to denote variables.
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
PDF
Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
PDF
Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
PDF
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
PDF
Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
PDF
Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
PDF
Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
PDF
Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
PDF
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
PDF
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
PDF
Are generative models fair? A study of racial bias in dermatological image generation
M. López-Pérez, S. Hauberg, A. Feragen
Scandinavian Conference on Image Analysis (SCIA), 2025
A fusocelular skin dataset with whole slide images for deep learning models
R. del Amor*, M. López-Pérez*, P. Meseguer*, S. Morales, L. Terradez, J. Aneiros-Fernandez, J. Mateos, R. Molina, V. Naranjo
Scientific Data, 2025
PDF
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts
M. López-Pérez (CA), A. Morquecho-Delgado, A. Schmidt, F. Pérez-Bueno, A. Martín-Castro, J. Mateos, R. Molina
Computer Methods and Programs in Biomedicine, 2024
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Domain Adaptation for Unsupervised Cancer Detection: An application for skin Whole Slides Images from an interhospital dataset
N. García-de-la-Puente*, M. López-Pérez*, L. Launet, V. Naranjo
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images
N. Kanwal, M. López-Pérez, U. Kiraz, T. C. M. Zuiverloon, R. Molina, K. Engan
Computerized Medical Imaging and Graphics, 2024
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Learning from crowds for automated histopathological image segmentation
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, C. Felicelli, J. Goldstein, B. Vadasz, R. Molina, A. K. Katsaggelos
Computerized Medical Imaging and Graphics, 2024
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An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
J. Pérez-Cano (CA), Y. Wu, A. Schmidt, M. López-Pérez, P. Morales-Álvarez, R. Molina, A. K. Katsaggelos
Expert Systems with Applications, 2024
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Unsupervised Prediction of Blastocyst Development from Oocyte images
N. P. García-de-la-Puente, E. Paya-Bosch, L. Murria, M. López-Pérez, M. Meseguer, V. Naranjo
DSA International Summer Conference, 2024
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
R. del Amor*, J. Pérez-Cano*, M. López-Pérez* (CA), L. Terradez, J. Aneiros-Fernandez, S. Morales, J. Mateos, R. Molina, V. Naranjo
Artificial Intelligence in Medicine, 2023
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Crowdsourcing segmentation of histopathological images using annotations provided by medical students
M. López-Pérez, P. Morales-Álvarez, L. AD Cooper, R. Molina, A. K Katsaggelos
International Conference on Artificial Intelligence in Medicine (AIME), 2023
Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
M. López-Pérez (CA), P. Morales-Álvarez, L. A. D. Cooper, R. Molina, A. K. Katsaggelos
IEEE Access, 2023
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Deep Gaussian Processes for Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
M. López-Pérez (CA), A. Schmidt, Y. Wu, R. Molina, A. K. Katsaggelos
Computer Methods and Programs in Biomedicine, 2022
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Learning from crowds in digital pathology using scalable variational Gaussian processes
M. López-Pérez, M. Amgad, P. Morales-Álvarez, P. Ruiz, L. A. D. Cooper (CA), R. Molina, A.K. Katsaggelos
Scientific Reports, 2021
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A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
M. López-Pérez (CA), L. García, C. Benítez, R. Molina
IEEE Transactions on Geoscience and Remote Sensing, 2021
A TV-based image processing framework for blind color deconvolution and classification of histological images
F. Pérez-Bueno (CA), M. López-Pérez, M. Vega, J. Mateos, V. Naranjo, R. Molina, A. K. Katsaggelos
Digital Signal Processing, 2020
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Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor
M. López-Pérez, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2019
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Á. Esteban*, M. López-Pérez (CA)*, A. Colomer, M. A. Sales, R. Molina, V. Naranjo
Computer Methods and Programs in Biomedicine, 2019
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