Data-Parallel MRI Brain Segmentation in Clinical Use
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Structural MRI brain analysis and segmentation is a crucial part in the daily routine in neurosurgery for intervention planning. Exemplarily, the free software FSL-FAST (FMRIB’s Segmentation Library – FMRIB’s Automated Segmentation Tool) in version 4 is used for segmentation of brain tissue types. To speed up the segmentation procedure by parallel execution, we transferred FSL-FAST to a General Purpose Graphics Processing Unit (GPGPU) using Open Computing Language (OpenCL) [1]. The necessary steps for parallelization resulted in substantially different and less useful results. Therefore, the underlying methods were revised and adapted yielding computational overhead. Nevertheless, we achieved a speed-up factor of 3.59 from CPU to GPGPU execution, as well providing similar useful or even better results.
[1] J. Besag. On the Statistical Analysis of Dirty Pictures , 1986 .
[2] James Demmel,et al. IEEE Standard for Floating-Point Arithmetic , 2008 .
[3] Nicholas J. Higham,et al. The Accuracy of Floating Point Summation , 1993, SIAM J. Sci. Comput..
[4] Stephen M. Smith,et al. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.