Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis. - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis.

Résumé

Colorectal cancer is the second cause of cancer death in United States: precursor lesions (polyps) detection is key for patient survival. Though colonoscopy is the gold standard screening tool, some polyps are still missed. Several computational systems have been pro- posed but none of them are used in the clinical room mainly due to com- putational constraints. Besides, most of them are built over still frame databases, decreasing their performance on video analysis due to the lack of output stability and not coping with associated variability on image quality and polyp appearance. We propose a strategy to adapt these methods to video analysis by adding a spatio-temporal stability mod- ule and studying a combination of features to capture polyp appearance variability. We validate our strategy, incorporated on a real-time detec- tion method, on a public video database. Resulting method detects all polyps under real time constraints, increasing its performance due to our adaptation strategy.
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Dates et versions

hal-01590659 , version 1 (19-09-2017)

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Citer

Quentin Angermann, Jorge J Bernal, Cristina Sánchez-Montes, Maroua Hammami, Gloria Fernández-Esparrach, et al.. Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis.. CARE 2017 (in conjunction with MICCAI 2017), Sep 2017, Québec City, Canada. pp.29-41, ⟨10.1007/978-3-319-67543-5_3⟩. ⟨hal-01590659⟩
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