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Journal of Electronic Imaging

Three-dimensional volume data segmentation using diffusion tensor-based superquadric analysis
Author(s): Sang Min Yoon
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Paper Abstract

A three-dimensional (3-D) segmentation technique is proposed, which separates the 3-D reconstructed volume data into several sub-regions having similar characteristics. This method is based on iteratively merging and splitting the sub-regions in the space of diffusion tensor fields. The superquadrics have been used as a figure of merit to measure the similarity between the neighboring voxels. By using the segmented 3-D in the magnetic resonance angiography data, we can efficiently visualize the vascular structure without any prior information as well as improve the medical diagnosis and therapy.

Paper Details

Date Published: 5 July 2013
PDF: 4 pages
J. Electron. Imag. 22(3) 030501 doi: 10.1117/1.JEI.22.3.030501
Published in: Journal of Electronic Imaging Volume 22, Issue 3
Show Author Affiliations
Sang Min Yoon, Kookmin Univ. (Korea, Republic of)

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