2003
DOI: 10.1117/12.481915
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Skeleton-based 3D computer-aided detection of colonic polyps

Abstract: In this paper, we propose a new computer aided detection (CAD) technique to utilize both global and local shape information of the colon wall for detection of colonic polyps. Firstly, the whole colon wall is extracted by our mixture-based image segmentation method. This method uses partial volume percentages to represent the distribution of different materials in each voxel, so it provides the most accurate information on the colon wall, especially the mucosa layer. Local geometrical measure of the colon mucos… Show more

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Cited by 9 publications
(15 citation statements)
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“…Therefore, the combination of both the traditional and the modified local shape measures in these filters is expected to reduce the miss classifications. Both Filter 1 and Filter 2 are very simple and work very well [42]. Experimental studies in this work show that both Filter 1 and Filter 2 can eliminate up to 80% miss classifications.…”
Section: Filtermentioning
confidence: 89%
See 3 more Smart Citations
“…Therefore, the combination of both the traditional and the modified local shape measures in these filters is expected to reduce the miss classifications. Both Filter 1 and Filter 2 are very simple and work very well [42]. Experimental studies in this work show that both Filter 1 and Filter 2 can eliminate up to 80% miss classifications.…”
Section: Filtermentioning
confidence: 89%
“…It is noted that both the traditional and the smoothed local curvatures have their complementary properties as described above [42]. A typical polyp shall show some geometrical attributes by the local and global GS measures.…”
Section: Filtermentioning
confidence: 90%
See 2 more Smart Citations
“…One CAD measure is the surface-or shape-based approach [47]. It combines both the traditional local principal curvature measures and a modified or smoothed version (which is called global principal curvature measures) to quantify the shape of the extracted mucosa layers from both ECC methods.…”
Section: Resultsmentioning
confidence: 99%