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Proceedings Paper

Computer-aided detection of initial polyp candidates with level set-based adaptive convolution
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Paper Abstract

In order to eliminate or weaken the interference between different topological structures on the colon wall, adaptive and normalized convolution methods were used to compute the first and second order spatial derivatives of computed tomographic colonography images, which is the beginning of various geometric analyses. However, the performance of such methods greatly depends on the single-layer representation of the colon wall, which is called the starting layer (SL) in the following text. In this paper, we introduce a level set-based adaptive convolution (LSAC) method to compute the spatial derivatives, in which the level set method is employed to determine a more reasonable SL. The LSAC was applied to a computer-aided detection (CAD) scheme to detect the initial polyp candidates, and experiments showed that it benefits the CAD scheme in both the detection sensitivity and specificity as compared to our previous work.

Paper Details

Date Published: 27 February 2009
PDF: 7 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72602T (27 February 2009); doi: 10.1117/12.811682
Show Author Affiliations
Hongbin Zhu, Stony Brook Univ. (United States)
Chaijie Duan, Stony Brook Univ. (United States)
Peking Univ. (China)
Zhengrong Liang, Stony Brook Univ. (United States)


Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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