@inproceedings{defeba6b99674f7bad1a5b990b6d9263,
title = "Computer-aided detection of initial polyp candidates with level setbased adaptive convolution",
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.",
keywords = "Adaptive convolution, Colonic polyps, Computer-aided detection, CT colonography, Geometric analysis, Level set",
author = "Zhu Hongbin and Duan Chaijie and Liang Zhengrong",
year = "2009",
doi = "10.1117/12.811682",
language = "English",
isbn = "9780819475114",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Medical Imaging 2009",
note = "Medical Imaging 2009: Computer-Aided Diagnosis ; Conference date: 10-02-2009 Through 12-02-2009",
}