| Autor: |
Maller JJ; General Electric Healthcare, Victoria.; Imaging and Phenotyping Laboratory, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, NSW.; Department of Psychiatry, Monash Alfred Psychiatry Research Centre, Victoria., Grieve SM; Imaging and Phenotyping Laboratory, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, NSW.; Department of Radiology, Royal Prince Alfred Hospital, Camperdown, Sydney, NSW., Vogrin SJ; Department of Neurology, Centre for Clinical Neuroscience and Neurological Research, St Vincent's Hospital, Fitzroy, Victoria, Australia., Welton T; Imaging and Phenotyping Laboratory, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, NSW. |
| Abstrakt: |
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 Project were processed on high-specification and regular workstations through three different configurations of 'eddy'. Processing times and graphics processing unit (GPU) resources used were monitored and compared. Using CUDA reduced the 'eddy' processing time by a factor of up to five. The CUDA slice-to-volume correction method was also faster than non-CUDA eddy except when datasets were large. We make a series of recommendations for eddy configuration and hardware. We suggest that users of eddy-correction software for dMRI processing utilise CUDA and take advantage of the slice-to-volume correction option. We recommend that users run eddy on computers with at least 32GB motherboard random access memory (RAM), and a graphics card with at least 4.5GB RAM and 3750 cores to optimise processing time. |
