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Proceedings Paper

Quantification of stenosis in coronary artery via CTA using fuzzy distance transform
Author(s): Yan Xu; Punam K. Saha; Guangshu Hu; Guoyuan Liang; Yan Yang; Jinzhao Geng
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Paper Abstract

tomographic angiography (CTA) being noninvasive, economical and informative, has become a common modality for monitoring disease status and treatment effects. Here, we present a new method for detecting and quantifying coronary arterial stenosis via CTA using fuzzy distance transform (FDT) approach. FDT computes local depth at each image point in the presence of partial voluming. Coronary arterial stenoses are detected and their severities are quantified by analyzing FDT values along the medial axis of an artery obtained by skeletonization. Also, we have developed a new skeletal pruning algorithm toward improving quality of medial axes and therefore, enhancing the accuracy of stenosis detection and quantification. The method is completed using the following steps - (1) fuzzy segmentation of coronary artery via CTA, (2) FDT computation of coronary arteries, (3) medial axis computation, (4) estimation of local diameter along arteries and (5) stenosis detection and quantification of arterial blockage. Performance of the method has been quantitatively evaluated on a realistic coronary artery phantom dataset with randomly simulated stenoses and the results are compared with a classical binary algorithm. The method has also been applied on a clinical CTA dataset from thirteen patients with 59 stenoses and the results are compared with an expert's quantitative assessment of stenoses. Results of the phantom experiment indicate that the new method is significantly more accurate as compared to the conventional binary method. Also, the results of the clinical study indicate that the computerized method is highly in agreement with the expert's assessments.

Paper Details

Date Published: 27 February 2009
PDF: 12 pages
Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 72620K (27 February 2009); doi: 10.1117/12.811361
Show Author Affiliations
Yan Xu, The Univ. of Iowa (United States)
Tsinghua Univ. (China)
Punam K. Saha, The Univ. of Iowa (United States)
Guangshu Hu, Tsinghua Univ. (China)
Guoyuan Liang, The Univ. of Iowa (United States)
Yan Yang, Georgia Institute of Technology (United States)
Jinzhao Geng, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 7262:
Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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