WM-DOVA maps for accurate polyp highlighting in colonoscopy

We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and...

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Bibliographic Details
Authors: Bernal del Nozal, Jorge|||0000-0001-8493-9514, Sánchez, F. Javier|||0000-0002-9364-3122, Fernández-Esparrach, Gloria|||0000-0002-3378-3940, Gil, Debora|||0000-0002-2770-4767, Rodríguez De Miguel, Cristina|||0000-0002-5576-0854, Vilariño, Fernando|||0000-0002-7705-4141
Format: article
Publication Date:2015
Country:España
Institution:Universitat Autònoma de Barcelona
Repository:Dipòsit Digital de Documents de la UAB
Language:English
OAI Identifier:oai:ddd.uab.cat:326494
Online Access:https://ddd.uab.cat/record/326494
https://dx.doi.org/urn:doi:10.1016/j.compmedimag.2015.02.007
Access Level:Open access
Keyword:Colonoscopy
Energy maps
Polyp localization
Saliency
Valley detection
Description
Summary:We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WM-DOVA (Window Median Depth of Valleys Accumulation) energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice.