Color Based Stool Region Detection in Colonoscopy Videos for Quality Measurements

• Published in: Advances in Image and Video Technology Vol. 7087; pp. 61 - 72
• Main Authors: Muthukudage, Jayantha, Oh, JungHwan, Tavanapong, Wallapak, Wong, Johnny, de Groen, Piet C.
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2011; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Colonoscopy; Image Classification; Medical Image Analysis; Region of Interest Detection
• ISBN: 9783642253669; 3642253660
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-25367-6_6

Colonoscopy is the accepted screening method for detecting colorectal cancer or colorectal polyps. One of the main factors affecting the diagnostic accuracy of colonoscopy is the quality of bowel preparation. Despite a large body of published data on methods that could optimize cleansing, a substantial level of inadequate cleansing occurs in 10% to 75% of patients in randomized controlled trials. In this paper, we propose a novel approach that automatically determines percentages of stool areas in images of digitized colonoscopy video files, and automatically computes an estimate of the BBPS (Boston Bowel Preparation Scale) score based on the percentages of stool areas. It involves the classification of image pixels based on their color features using a new method of planes on RGB (Red, Green and Blue) color space. Our experiments show that the proposed stool classification method is sound and very suitable for colonoscopy video analysis where variation of color features is considerably high.