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Abstract #1886

Acceleration Strategy for Navigated Diffusion Imaging

Bruno Madore1, Jr-Yuan Chiou1, Renxin Chu1, Tzu-Cheng Chao2, Stephan E. Maier1

1Department of Radiology, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, United States; 2Department of Computer Science and Information Engineering, National Cheng-Kung University, Tainan, Taiwan

A fast-imaging strategy is presented, to accelerate data acquisition in segmented MR diffusion imaging. Navigator echoes are typically employed to correct for motion effects in multi-shot diffusion imaging. A spatially-smooth representation of the object is obtained from a small region around k-space center, and only phase information is used for motion correction. On the other hand, in the field of accelerated MRI, spatially-smooth signal is often called prior knowledge, and only magnitude information in an x-y-frequency space is used for regularization purposes. The proposed approach fully exploits the available navigator signal, phase and magnitude, toward accelerated motion-corrected diffusion imaging.

Keywords

accelerated acceleration acknowledged acquisition affect aliasing almost amount amounts anisotropy artifacts assumed available benefits called central channel coefficient coil combining compatible compensation compressed computer conditioning contribute correct corrected correction corrupted damped decay diagonal differs diffusion discarded distortion duals effective elements emphasize employed encoding engineering entirely exemplified expressed feature fold fractional free frequency full fully grant hand handled head healthy heavily hospital implementation index interleaved knowledge least made magnitude maier makes matrix medical models mostly motion much national navigated navigator object parallel part performance preferred prior problem processing proposed quadrature radiology randomized readily reason reconstructed reduce reduced reduction regular regularization related representation represented respectively sampled sampling scheme schemes school science segmented segments sensing sensitivity several shot slice smooth solution solved space sparse spatial square strategy subsamples suffered summation support suppressed system tends term transform transforms trivial typically usual volunteer ways women yuan