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Journal of Electronic Imaging • Open Access

Automatic centerline detection of small three-dimensional vessel structures
Author(s): Yuanzhi Cheng; Xin Hu; Yadong Wang; Jinke Wang; Shinichi Tamura

Paper Abstract

Vessel centerline detection is very important in many medical applications. In the noise and low-contrast regions, most existing methods may only produce an incomplete and disconnected extraction of the vessel centerline if no user guidance is provided. A robust and automatic method is described for extraction of the vessel centerline. First, we perform small vessel enhancement by processing with a set of line detection filters, corresponding to the 13 orientations; for each voxel, the highest filter response is kept and added to the image. Second, we extract vessel centerline segment candidates by a thinning algorithm. Finally, a global optimization algorithm is employed for grouping and selecting vessel centerline segments. We validate the proposed method quantitatively on a number of synthetic data sets, the liver artery and lung vessel. Comparisons are made with two state-of-the-art vessel centerline extraction methods and manual extraction. The experiments show that our method is more accurate and robust that these state-of-the-art methods and is, therefore, more suited for automatic vessel centerline extraction.

Paper Details

Date Published: 21 January 2014
PDF: 13 pages
J. Electron. Imaging. 23(1) 013007 doi: 10.1117/1.JEI.23.1.013007
Published in: Journal of Electronic Imaging Volume 23, Issue 1
Show Author Affiliations
Yuanzhi Cheng, Harbin Institute of Technology (China)
Xin Hu, Harbin Institute of Technology (China)
Yadong Wang, Harbin Institute of Technology (China)
Jinke Wang, Harbin Institute of Technology (China)
Shinichi Tamura, Osaka Univ. (Japan)


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