14 February 2012 A fuzzy clustering vessel segmentation method incorporating line-direction information
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Abstract
A data clustering based vessel segmentation method is proposed for automatic liver vasculature segmentation in CT images. It consists of a novel similarity measure which incorporates the spatial context, vesselness information and line-direction information in a unique way. By combining the line-direction information and spatial information into the data clustering process, the proposed method is able to take care of the fine details of the vessel tree and suppress the image noise and artifacts at the same time. The proposed algorithm has been evaluated on the real clinical contrast-enhanced CT images, and achieved excellent segmentation accuracy without any experimentally set parameters.
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Zhimin Wang, Zhimin Wang, Wei Xiong, Wei Xiong, Weimin Huang, Weimin Huang, Jiayin Zhou, Jiayin Zhou, Sudhakar K. Venkatesh, Sudhakar K. Venkatesh, "A fuzzy clustering vessel segmentation method incorporating line-direction information", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83143I (14 February 2012); doi: 10.1117/12.919106; https://doi.org/10.1117/12.919106
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