Accelerating the Diffusion-Weighted Imaging Biomarker in the clinical practice: comparative study

Diffusion Weighted Imaging (DWI) methods (ADC and IVIM models) extract meaningful information about the microscopic motions of water of human tissues from MRIs. This is a non invasive method which plays an important role in the diagnosis of ischemic strokes, high grade gliomas or tumors. In the La Fe Polytechnic and University Hospital, the DWI methods aforementioned are used in clinical practice and Matlab is used as a development tool for his out of box performance and fast prototyping. However, each image takes hours to compute due to Matlab's environment and interpreted functions. Because of this, its use in clinical practice is limited. In this paper we present three compiled versions on which different parallel paradigms based on multicore (OpenMP) and GPU (CUDA) are applied. These implementations have managed to reduce the computation time to less than one minute, therefore, it allows easing their use in daily clinical practice at a cheap acquisition cost. (C) 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the International Conference on Computational Science