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Abstract #3332

Joint Non-local Means Reconstruction for Correction of Phase-Induced Errors in Diffusion Tensor Imaging

Sevgi Gokce Kafali1,2, Tolga Cukur1,2, and Emine Ulku Saritas1,2

1Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey, 2National Magnetic Resonance Research Center (UMRAM), Ankara, Turkey

Multiple acquisitions have to be averaged to achieve reasonable signal-to-noise ratio (SNR) in high-resolution diffusion tensor imaging (DTI). However, involuntary global/local motions during diffusion-sensitizing gradients create k-space shifts, and global/local phase differences between different acquisitions, complicating image reconstruction. In this work, we propose a phase-correcting joint non-local means reconstruction that effectively prevents phase cancellations and reduces noise. This technique jointly utilizes the images from different diffusion-encoding directions to preserve the fractional anisotropy (FA) map. Results are demonstrated for in vivo spinal cord DTI and on a simulated DTI dataset.

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