858 citations · 1.2k across the 19 of their papers we have counts for
10 papers · 1 filter
A self-training framework for glaucoma grading in OCT B-scans
Gabriel García, Adrián Colomer, Rafael Verdú-Monedero +2
In this paper, we present a self-training-based framework for glaucoma grading using OCT B-scans under the presence of domain shift. Particularly, the proposed two-step learning me…
Looking at the whole picture: constrained unsupervised anomaly segmentation
Julio Silva-Rodríguez, Valery Naranjo, Jose Dolz
Current unsupervised anomaly localization approaches rely on generative models to learn the distribution of normal images, which is later used to identify potential anomalous regio…
A Novel Self-Learning Framework for Bladder Cancer Grading Using Histopathological Images
Gabriel García, Anna Esteve, Adrián Colomer +2
Recently, bladder cancer has been significantly increased in terms of incidence and mortality. Currently, two subtypes are known based on tumour growth: non-muscle invasive (NMIBC)…
Circumpapillary OCT-Focused Hybrid Learning for Glaucoma Grading Using Tailored Prototypical Neural Networks
Gabriel García, Rocío del Amor, Adrián Colomer +3
Glaucoma is one of the leading causes of blindness worldwide and Optical Coherence Tomography (OCT) is the quintessential imaging technique for its detection. Unlike most of the st…
Prostate Gland Segmentation in Histology Images via Residual and Multi-Resolution U-Net
Julio Silva-Rodríguez, Elena Payá-Bosch, Gabriel García +2
Prostate cancer is one of the most prevalent cancers worldwide. One of the key factors in reducing its mortality is based on early detection. The computer-aided diagnosis systems f…
Going Deeper through the Gleason Scoring Scale: An Automatic end-to-end System for Histology Prostate Grading and Cribriform Pattern Detection
Julio Silva-Rodríguez, Adrián Colomer, María A. Sales +2
The Gleason scoring system is the primary diagnostic and prognostic tool for prostate cancer. In recent years, with the development of digitisation devices, the use of computer vis…
WeGleNet: A Weakly-Supervised Convolutional Neural Network for the Semantic Segmentation of Gleason Grades in Prostate Histology Images
Julio Silva-Rodríguez, Adrián Colomer, Valery Naranjo
Prostate cancer is one of the main diseases affecting men worldwide. The Gleason scoring system is the primary diagnostic tool for prostate cancer. This is obtained via the visual…
Self-learning for weakly supervised Gleason grading of local patterns
Julio Silva-Rodríguez, Adrián Colomer, Jose Dolz +1
Prostate cancer is one of the main diseases affecting men worldwide. The gold standard for diagnosis and prognosis is the Gleason grading system. In this process, pathologists manu…
An Attention-based Weakly Supervised framework for Spitzoid Melanocytic Lesion Diagnosis in WSI
Rocío del Amor, Laëtitia Launet, Adrián Colomer +4
Melanoma is an aggressive neoplasm responsible for the majority of deaths from skin cancer. Specifically, spitzoid melanocytic tumors are one of the most challenging melanocytic le…
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation
del Amor Rocío, Colomer Adrián, Monteagudo Carlos +1
Epigenetic alterations have an important role in the development of several types of cancer. Epigenetic studies generate a large amount of data, which makes it essential to develop…