Magnetic resonance brain volume property-based accelerate medical image algorithms using graphics processing unit. (10th February 2022) - Sriramakrishnan, P.; Kalaiselvi, T.
This paper elaborates the design and implementation details of parallel image processing techniques that are used to accelerate the medical image algorithms with compute unified device architecture (CUDA) supported graphics processing unit (GPU). The algorithms are chosen from denoising, morphology, clustering, and segmentation. Three parallel computing models are developed based on the properties of algorithms and magnetic resonance imaging (MRI) principles. The acceleration of parallel algorithms is compared with that of sequential central processing unit (CPU) implementation measured in terms of speedup folds (×).