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Proceedings Paper

Skeleton-based 3D computer-aided detection of colonic polyps
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Paper 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 mucosa layer is defined by the curvature and gradient information extracted from the segmented colon-wall mixture data. Global shape information is provided by applying an improved linear integral convolution operation to the mixture data. The CAD technique was tested on twenty patient datasets. The local geometrical measure extracted from the mixture segmentation represents more accurately the polyp variation than that extracted from conventional label classification, leading to improved detection. The added global shape information further improves the polyp detection.

Paper Details

Date Published: 15 May 2003
PDF: 11 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481915
Show Author Affiliations
Zigang Wang, SUNY/Stony Brook (United States)
Lihong Li, SUNY/Stony Brook (United States)
Xiang Li, SUNY/Stony Brook (United States)
Zhengrong Liang, SUNY/Stony Brook (United States)
Donald P. Harrington, SUNY/Stony Brook (United States)


Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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