Saliency Maps of Video-colonoscopy Images for the Analysis of Their Content and the Prevention of Colorectal Cancer Risks

Valentine Wargnier-Dauchelle, Camille Simon-Chane, Aymeric Histace

2020

Abstract

The detection and removal of adenomatous polyps via colonoscopy is the gold standard for the prevention of colon cancer. Indeed, polyps are at the origins of colorectal cancer which is one of the deadliest diseases in the world. This article aims to contribute to the wide range of methods already developed for the prevention of colorectal cancer risks. For this, the work is organized around the detection and the localization of polyps in video-colonoscopy images. The aim of this paper is to find the best description of a bowel image in order to classify a patch, that is to say a image fragment, as polyp or not. The classification is achieved thanks to an SVM (Support Vector Machine) using a bag of features. Different types of features extraction will be compared. Thus, the traditional SURF (Speeded-Up Robust Features) extractor will be compared to local features extractors like HOG (Histogram of Oriented Gradient) and LBP (Local Binary Pattern) but also to an original extractor based on the structural entropy.

Paper Citation

in Harvard Style

Wargnier-Dauchelle V., Simon-Chane C. and Histace A. (2020). Saliency Maps of Video-colonoscopy Images for the Analysis of Their Content and the Prevention of Colorectal Cancer Risks. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS; ISBN 978-989-758-398-8, SciTePress, pages 106-114. DOI: 10.5220/0009148401060114

in Bibtex Style

@conference{biosignals20,
author={Valentine Wargnier-Dauchelle and Camille Simon-Chane and Aymeric Histace},
title={Saliency Maps of Video-colonoscopy Images for the Analysis of Their Content and the Prevention of Colorectal Cancer Risks},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS},
year={2020},
pages={106-114},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009148401060114},
isbn={978-989-758-398-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 4: BIOSIGNALS
TI - Saliency Maps of Video-colonoscopy Images for the Analysis of Their Content and the Prevention of Colorectal Cancer Risks
SN - 978-989-758-398-8
AU - Wargnier-Dauchelle V.
AU - Simon-Chane C.
AU - Histace A.
PY - 2020
SP - 106
EP - 114
DO - 10.5220/0009148401060114
PB - SciTePress