Journal article

Performance gains with Compute Unified Device Architecture-enabled eddy current correction for diffusion MRI.

Jerome J Maller, Stuart M Grieve, Simon J Vogrin, Thomas Welton

Neuroreport | LIPPINCOTT WILLIAMS & WILKINS | Published : 2020

Abstract

Correcting for eddy currents, movement-induced distortion and gradient inhomogeneities is imperative when processing diffusion MRI (dMRI) data, but is highly computing resource-intensive. Recently, Compute Unified Device Architecture (CUDA) was implemented for the widely-used eddy-correction software, 'eddy', which reduces processing time and allows more comprehensive correction. We investigated processing speed, performance and compatibility of CUDA-enabled eddy-current correction processing compared to commonly-used non-CUDA implementations. Four representative dMRI datasets from the Human Connectome Project, Alzheimer's Disease Neuroimaging Initiative and Chronic Diseases Connectome Proje..

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