J
Jorge Bernal
Researcher at Autonomous University of Barcelona
Publications - 48
Citations - 2537
Jorge Bernal is an academic researcher from Autonomous University of Barcelona. The author has contributed to research in topics: Segmentation & Image segmentation. The author has an hindex of 15, co-authored 45 publications receiving 1428 citations. Previous affiliations of Jorge Bernal include University of Alabama at Birmingham.
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Journal ArticleDOI
WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians
Jorge Bernal,F. Javier Sánchez,Gloria Fernández-Esparrach,Debora Gil,Cristina Rodríguez,Fernando Vilariño +5 more
TL;DR: This paper introduces a novel polyp localization method for colonoscopy videos based on a model of appearance for polyps which defines polyp boundaries in terms of valley information and proves that this method outperforms state-of-the-art computational saliency results.
Journal ArticleDOI
Towards automatic polyp detection with a polyp appearance model
TL;DR: The method consists of three stages: region segmentation, region description and region classification, which guarantees that if a polyp is present in the image, it will be exclusively and totally contained in a single region.
Journal ArticleDOI
Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results From the MICCAI 2015 Endoscopic Vision Challenge
Jorge Bernal,Nima Tajkbaksh,Francisco Javier Sánchez,Bogdan J. Matuszewski,Hao Chen,Lequan Yu,Quentin Angermann,Olivier Romain,Bjorn Rustad,Ilangko Balasingham,Konstantin Pogorelov,Sungbin Choi,Quentin Debard,Lena Maier-Hein,Stefanie Speidel,Danail Stoyanov,Patrick Brandao,Henry Córdova,Cristina Sánchez-Montes,Suryakanth R. Gurudu,Gloria Fernández-Esparrach,Xavier Dray,Jianming Liang,Aymeric Histace +23 more
TL;DR: Results show that convolutional neural networks are the state of the art in polyp detection and it is also demonstrated that combining different methodologies can lead to an improved overall performance.
Journal ArticleDOI
A benchmark for endoluminal scene segmentation of colonoscopy images
David Vazquez,David Vazquez,Jorge Bernal,F. Javier Sánchez,Gloria Fernández-Esparrach,Antonio M. López,Antonio M. López,Adriana Romero,Michal Drozdzal,Aaron Courville +9 more
TL;DR: A comparative study is performed to show that FCNs significantly outperform, without any further postprocessing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization.
Journal ArticleDOI
Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps.
Gloria Fernández-Esparrach,Jorge Bernal,María López-Cerón,Henry Córdova,Cristina Sánchez-Montes,Cristina Rodríguez de Miguel,Francisco Javier Sánchez +6 more
TL;DR: Energy maps performed well for colonic polyp detection, indicating their potential applicability in clinical practice, and relied on a model that defines polyp boundaries as valleys of image intensity.