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Abstract #4473

A Novel Post-processing Procedure to Sharpen the ODFs of Different HARDI Datasets by Using Super-CSD

Shiou-Ping Lee 1 , Chung-Ming Chen 2 , Li-Chun Hsieh 1 , Wing-Keung Cheung 1 , Yu-Chiang Chen 1 , and Ming-Chung Chou 3

1 Department of Medical imaging, Far Eastern Memorial hospital, Banqiao, New Taipei city, Taiwan, 2 Insitute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan, 3 Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan

Recently, there were a variety of algorithms proposed to reconstruct orientation distribution function based on high angular resolution diffusion imaging data in order to resolve multiple fiber orientations. However, it was found that some fiber orientations were likely lost when fibers intersected at a small angle. A previous study performed the super resolved - constrained spherical deconvolution to resolve multiple fiber orientations crossing at a smaller angle, but the method was only suitable for diffusion-weighted datasets acquired in a spherical coordinate, such as q-ball imaging. Other HARDI datasets, such as diffusion spectrum imaging, acquired in a Cartestian coordinate whose fiber orientation distribution could not be obtained by using super-CSD. Hence, the purpose of this study is to propose a post-processing procedure which is suitable for sharpening ODFs of different HARDI datasets and resolving multiple fiber orientations by using super-CSD.

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