Accelerating Fibre Orientation Estimation from Diffusion Weighted Magnetic Resonance Imaging Using GPUs

Diffusion Weighted Magnetic Resonance Imaging (DW-MRI) and tractography approaches are the only tools that can be utilized to estimate structural connections between different brain areas, non-invasively and in-vivo. A first step that is commonly utilized in these techniques includes the estimation of the underlying fibre orientations and their uncertainty in each voxel of the image. A popular method to achieve that is implemented in the FSL software, provided by the FMRIB Centre at University of Oxford, and is based on a Bayesian inference framework. Despite its popularity, the approach has high computational demands, taking normally more than 24 hours for analyzing a single subject. In this paper, we present a GPU-optimized version of the FSL tool that estimates fibre orientations. We report up to 85x of speed-up factor between the GPU and its sequential counterpart CPU-based version.

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