Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-25367-6_6 | PSIVT (1) |
Keywords | Field | DocType |
color feature,stool area,colorectal polyp,accepted screening method,proposed stool classification method,colonoscopy video analysis,new method,color space,colorectal cancer,digitized colonoscopy video file,stool region detection,quality measurement,image classification | Computer vision,Boston bowel preparation scale,Color space,Colonoscopy,Pattern recognition,Computer science,RGB color model,Pixel,Artificial intelligence,Region detection,Contextual image classification,Colorectal cancer | Conference |
Volume | ISSN | Citations |
7087 | 0302-9743 | 3 |
PageRank | References | Authors |
0.43 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jayantha Muthukudage | 1 | 27 | 2.14 |
| JungHwan Oh | 2 | 520 | 44.87 |
| Wallapak Tavanapong | 3 | 535 | 63.27 |
| Johnny Wong | 4 | 500 | 49.19 |
| Piet C. De Groen | 5 | 372 | 29.89 |