JEI Letters

Three-dimensional volume data segmentation using diffusion tensor-based superquadric analysis

[+] Author Affiliations
Sang Min Yoon

Kookmin University, School of Computer Science, 77 Jeongneung-ro, Sungbuk-gu, Seoul 136-702, Republic of Korea

J. Electron. Imaging. 22(3), 030501 (Jul 05, 2013). doi:10.1117/1.JEI.22.3.030501
History: Received March 12, 2013; Revised May 20, 2013; Accepted June 12, 2013
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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.

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Topics

Diffusion

Citation

Sang Min Yoon
"Three-dimensional volume data segmentation using diffusion tensor-based superquadric analysis", J. Electron. Imaging. 22(3), 030501 (Jul 05, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.3.030501


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