Efficient CT Image Reconstruction in a GPU Parallel Environment.

ABSTRACT: Computed tomography is nowadays an indispensable tool in medicine used to diagnose multiple diseases. In clinical and emergency room environments, the speed of acquisition and information processing are crucial. CUDA is a software architecture used to work with NVIDIA graphics processing units. In this paper a methodology to accelerate tomographic image reconstruction based on maximum likelihood expectation maximization iterative algorithm and combined with the use of graphics processing units programmed in CUDA framework is presented. Implementations developed here are used to reconstruct images with clinical use. Timewise, parallel versions showed improvement with respect to serial implementations. These differences reached, in some cases, 2 orders of magnitude in time while preserving i

SUBMITTER: Valencia Perez TA 

PROVIDER: S-EPMC7138519 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature