5 July 2013 Three-dimensional volume data segmentation using diffusion tensor-based superquadric analysis
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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.
© 2013 SPIE and IS&T
Sang Min Yoon, 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 . Submission:
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