TY - GEN
T1 - Color based stool region detection in colonoscopy videos for quality measurements
AU - Muthukudage, Jayantha
AU - Oh, Junghwan
AU - Tavanapong, Wallapak
AU - Wong, Johnny
AU - De Groen, Piet C.
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - Colonoscopy
KW - Image Classification
KW - Medical Image Analysis
KW - Region of Interest Detection
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U2 - 10.1007/978-3-642-25367-6_6
DO - 10.1007/978-3-642-25367-6_6
M3 - Conference contribution
AN - SCOPUS:82155185341
SN - 9783642253669
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 61
EP - 72
BT - Advances in Image and Video Technology - 5th Pacific Rim Symposium, PSIVT 2011, Proceedings
T2 - 5th Pacific-Rim Symposium on Video and Image Technology, PSIVT 2011
Y2 - 20 November 2011 through 23 November 2011
ER -