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

Sang Min Yoon

doi:10.1117/1.JEI.22.3.030501

5 July 2013 Three-dimensional volume data segmentation using diffusion tensor-based superquadric analysis

Sang Min Yoon

Author Affiliations +

Journal of Electronic Imaging, Vol. 22, Issue 3, 030501 (July 2013). https://doi.org/10.1117/1.JEI.22.3.030501

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.

Citation Download Citation

Sang Min Yoon "Three-dimensional volume data segmentation using diffusion tensor-based superquadric analysis," Journal of Electronic Imaging 22(3), 030501 (5 July 2013). https://doi.org/10.1117/1.JEI.22.3.030501

Published: 5 July 2013

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