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Proceedings Paper

Hepatic vessel segmentation from computed tomography using three-dimensional hyper-complex edge detection operator
Author(s): Yang Ma; Xingmin Li
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Paper Abstract

This paper proposes a three-dimensional(3D) segmentation algorithm using hyper-complex edge detection operator and applies the new algorithm to three-dimensional hepatic vessel segmentation from computed tomography (CT) volumetric data. A 3D hyper-complex edge detection operator is constructed by combining octonion and gradient operator. We replace every voxel of the volumetric data by one octonion which consist of its gray-level and its 6 neighborhoods' gray-level. Via this the original volumetric data is defined as octonion volumetric data. Similar to the Sobel operator, there are three principal directions (coordinate axes) in 3D hyper-complex edge detection operator, and each element in this operator is a octonion. The operator is circularly convoluted with octonion volumetric data to get the value of matching response. If matched, this voxel is the edge of vessel. Experimental results show that the algorithm can effectively segment small vascular tree branches.

Paper Details

Date Published: 10 January 2014
PDF: 6 pages
Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 90690K (10 January 2014); doi: 10.1117/12.2050193
Show Author Affiliations
Yang Ma, South China Normal Univ. (China)
Xingmin Li, South China Normal Univ. (China)

Published in SPIE Proceedings Vol. 9069:
Fifth International Conference on Graphic and Image Processing (ICGIP 2013)
Yulin Wang; Xudong Jiang; Ming Yang; David Zhang; Xie Yi, Editor(s)

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