Polyp Segmentation in NBI Colonoscopy

Endoscopic screening of the colon (colonoscopy) is performed to prevent cancer and to support therapy. During intervention colon polyps are located, inspected and, if need be, removed by the investigator. We propose a segmentation algorithm as a part of an automatic polyp classification system for colonoscopic Narrow-Band images. Our approach includes multi-scale filtering for noise reduction, suppression of small blood vessels, and enhancement of major edges. Results of the subsequent edge detection are compared to a set of elliptic templates and evaluated. We validated our algorithm on our polyp database with images acquired during routine colonoscopic examinations. The presented results show the reliable segmentation performance of our method and its robustness to image variations.

• Type: Conference
• Year: 2009
• Where: BILDMED
• Authors: Sebastian Gross, Manuel Kennel, Thomas Stehle, Jonas Wulff, Jens Tischendorf, Christian Trautwein, Til Aach
• Keywords: Automatic Polyp Classification, BILDMED 2007, BILDMED 2009, Intervention Colon Polyps, Segmentation Algorithm