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Abstract #3178

A k-D Space Acceleration Strategy for HARDI with Compressed Sensing

Tzu-Cheng Chao1, 2, Jr-Yuan Chiou3, Cheng-Wen Ko4, Ming-Ting Wu5, Stephan E. Maier3, Bruno Madore3

1Department of Computer Science and Information Engineering, National Cheng-Kung University, Tainan, Taiwan; 2Institute of Medical Informatics, National Cheng-Kung University, Tainan, Taiwan; 3Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; 4Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan; 5Department of Radiology, Kaohsiung Veteran General Hospital, Kaohsiung, Taiwan

An accelerated sampling strategy is proposed that can effectively reduce both geometric distortion and scan time in the context of the high Angularly Resolved Diffusion Imaging(HARDI) diffusion-weighted imaging method. The approach combines sampling strategies inspired from accelerated dynamic imaging and from the rossing Fiber Angular Resolution of Intra-Voxel structure (CFRI) algorithm to resolve crossing fibers in a manner that is fast and fairly insensitive to susceptibility-induced field variations and geometric distortion.

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Keywords

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