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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