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.
Keywords: Colonoscopy images; Feature classification; Feature selection; Image processing; Polyp detection.
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