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Proceedings Paper

Automatic segmentation of the coronary artery in MSCT volume data
Author(s): Shengjun Wang; Yong Yue; Yan Kang; Jiren Liu
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Paper Abstract

Extracting coronary artery is one of the vital steps in the analysis process based on the modality of computed tomography angiography (CTA), the aim of which is to recognize coronary artery from 3D volume data, and then provide evidences of analysis and quantitative measurement information for coronary artery computer aided detection. According to the structure features of coronary artery angiography scanned by multiple slices computed tomography (MSCT), an automatic segmentation algorithm is proposed. Firstly, detect and recognize the multiple seed points of the coronary artery in the scale space automatically from the 3D complex cardiac image datasets. Secondly, an improved layer region growing algorithm oriented to 3D tubular structure tissues is proposed to segment the coronary artery. Experiments show that the algorithm can extract coronary artery vessels effectively, which can improve the automation of coronary artery analysis, thus improve physicians' work efficiency.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 74971V (30 October 2009); doi: 10.1117/12.828644
Show Author Affiliations
Shengjun Wang, Northeastern Univ. (China)
Neusoft Medical Systems Co., Ltd. (China)
Yong Yue, Shengjing Hospital of China Medical Univ. (China)
Yan Kang, Northeastern Univ. (China)
Neusoft Medical Systems Co., Ltd. (China)
Jiren Liu, Northeastern Univ. (China)


Published in SPIE Proceedings Vol. 7497:
MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques
Faxiong Zhang; Faxiong Zhang, Editor(s)

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