Page Archive

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
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
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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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