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An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection
We propose an end2end method combining attention and Gaussian processes. We apply it to intracraneal hemorrhage detection.
Jose Pérez-Cano, Yunan Wu, Arne schmidt, Miguel López-Pérez, Pablo Morales-Álvarez, Rafael Molina, Aggelos K. Katsaggelos
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Are you sure it’s an artifact? Artifact detection and uncertainty quantification in histological images
We propose a method for artifact detection in histopathological images. We quantify the uncertainty on the predictions.
Neel Kanwal, Miguel López-Pérez, Umay Kiraz, Tahlita C.M. Zuiverloon, Rafael Molina, Kjersti Engan
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Learning from crowds for automated histopathological image segmentation
We propose new method for histopathological image segmentation using multiple non-expert annotators.
Miguel López-Pérez, Pablo Morales-Álvarez, Lee A. D. Cooper, Christopher Felicelli, Jeffery Goldstein, Brian Vadasz, Rafael Molina, Aggelos K. Katsaggelos
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Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset
We propose a new dataset of histopathological skin images annotated by several non-expert annotators.
Jose Pérez-Cano, Rocío del Amor, Miguel López-Pérez, Liria Terradez, Jose Aneiros-Fernández, Sandra Morales, Javier Mateos, Rafael Molina, Valery Naranjo
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Deep Gaussian Processes for classification with multiple noisy annotators. Application to breast cancer tissue classification
We propose Deep Gaussian Processses for crowdsourcing. We apply them to tissue classification in digital pathology.
Miguel López-Pérez, Pablo Morales-Álvarez, Lee A. D. Cooper, Rafael Molina, Aggelos K. Katsaggelos
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Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection
We propose Deep Gaussian Processses for Multiple Instance Learning.
Miguel López-Pérez, Arne schmidt, Yunan Wu, Rafael Molina, Aggelos K. Katsaggelos
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Learning from crowds in digital pathology using scalable variational Gaussian processes
We propose Gaussian Processses for crowdsourcing in digital pathology.
Miguel López-Pérez, Mohamed Amgad, Pablo Morales-Álvarez, Pablo Ruiz, Lee A. D. Cooper, Rafael Molina, Aggelos K. Katsaggelos
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A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes
Miguel López-Pérez, Luz García, Carmen Benítez, Rafael Molina
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A TV-based image processing framework for blind color deconvolution and classification of histological images
A new color normalization method for histopathological images. This bayesian method is based on Total Variation.
Fernando Pérez-Bueno, Miguel López-Pérez, Miguel Vega, Javier Mateos, Valery Naranjo, Rafael Molina, Aggelos K. Katsaggelos
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A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes
Ángel E. Esteban, Miguel López-Pérez, Adrián Colomer, María A. Sales, Rafael Molina, Valery Naranjo
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