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Colon Polyp Segmentation Using Texture Analysis

In recent years, there has been an increase in the number of detected cases of colon cancer. This is largely due to the increasing use of colorectal screening. The number of colonoscopies performed has consequently risen, leading to specialists often being overburdened by the increasing workload. In an attempt to provide assistance with medical diagnosis, algorithms have been developed which enable the automated detection of polyps in colonoscopy images via the analysis of their texture. This aims to reduce the missed polyp rate, which is the main problem regarding colonoscopy. The system designed herein has obtained an 89.21% polyp detection rate, and 93.9% and 87.31% segmentation quality for the annotated area covered and Dice coefficient indicators, respectively. The development of this method aims to provide a support tool for medical diagnosis which has a positive impact on patient health.