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.
CITATION STYLE
Weber, J., Doenitz, C., Brawanski, A., & Palm, C. (2015). Data-parallel MRI brain segmentation in clinical use: Porting FSL-FASTv4 to GPGPUs. In Informatik aktuell (pp. 389–394). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-662-46224-9_67
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