Magnetic resonance brain volume property-based accelerate medical image algorithms using graphics processing unit. (10th February 2022)

• Record Type: Journal Article
• Authors: Sriramakrishnan, P.; Kalaiselvi, T.
• Is Part Of: International journal of biomedical engineering and technology. Volume 38:Number 2(2022)
• Page Start: 128
• Page End: 150
• Publication Date: 2022-02-10
• Subjects: graphics processing unit -- GPU -- compute unified device architecture -- CUDA -- parallel processing -- medical imaging -- brain volume -- bilateral filter -- non-local means -- NLM -- K-means clustering -- FCM; Biomedical engineering -- Periodicals; 610.28
• Languages: English
• ISSNs: 1752-6418

Abstract

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 (×).