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MICCAI
2009
Springer

A Two-Level Approach Towards Semantic Colon Segmentation: Removing Extra-Colonic Findings

10 years 7 months ago
A Two-Level Approach Towards Semantic Colon Segmentation: Removing Extra-Colonic Findings
Abstract. Computer aided detection (CAD) of colonic polyps in computed tomographic colonography has tremendously impacted colorectal cancer diagnosis using 3D medical imaging. It is a prerequisite for all CAD systems to extract the air-distended colon segments from 3D abdomen computed tomography scans. In this paper, we present a two-level statistical approach of first separating colon segments from small intestine, stomach and other extra-colonic parts by classification on a new geometric feature set; then evaluating the overall performance confidence using distance and geometry statistics over patients. The proposed method is fully automatic and validated using both the classification results in the first level and its numerical impacts on false positive reduction of extra-colonic findings in a CAD system. It shows superior performance than the state-of-art knowledge or anatomy based colon segmentation algorithms [1,2,3].
Le Lu, Matthias Wolf, Jianming Liang, Murat Dundar
Added 05 Mar 2010
Updated 08 Mar 2010
Type Conference
Year 2009
Where MICCAI
Authors Le Lu, Matthias Wolf, Jianming Liang, Murat Dundar, Jinbo Bi, Marcos Salganicoff
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