Related Experiment Video For Colonoscopy images
Updated: Feb 7, 2026

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
Published on: August 23, 2017
Automatized colon polyp segmentation via contour region analysis
Alain Sánchez-González1, Begonya García-Zapirain1, Daniel Sierra-Sosa2
1University of Deusto, eVida Research Group, Av. de las Universidades 24, Bilbao, 48007, Spain.
Abstract:
The increasing use of colorectal cancer screening programs has contributed to the growing number of colonoscopies performed by health centers. Hence, in recent years there has been a tendency to develop medical diagnosis support tools in order to assist specialists. This research has designed an automatized polyp detection system that allows a reduction in the rate of missed polyps that can lead to interval cancer; one of the main risks existing in colonoscopy. A characterization has therefore been made of the shape, color and curvature of edges and their regions, enabling the segmentation of polyps present in colonoscopy images. A 90.53% polyp detection rate has been achieved using the designed system, and 76.29% and 71.57% segmentation quality for the Annotated Area Covered and Dice Coefficient indicators respectively. This system aims to offer assistance with medical diagnosis that has a positive impact on patient health.
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