Work

Parallelization of iterative reconstruction algorithms in multiple modalities

Year: 2014

Type: conference-paper

Abstract: In this work we have parallelized the Maximum Likelihood Expectation-Maximization (MLEM) and Ordered Subset Expectation Maximization (OSEM) algorithms for improving efficiency of reconstructions of multiple pinholes SPECT, and cone-bean CT data. We implemented the parallelized versions of the algorithms on a General Purpose Graphic Processing Unit (GPGPU): 448 cores of a NVIDIA Tesla M2070 GPU with 6GB RAM per thread of computing. We compared their run times against those from the corresponding CPU implementations running on 8 cores CPU of an AMD Opteron 6128 with 32 GB RAM. We have further shown how an optimization of thread balancing can accelerate the speed of the GPU implementation.

Source: IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

DOI: 10.1109/nssmic.2014.7430944

Authors: Debasis Mitra, Hui Pan, Fares Alhassen, Youngho Seo

Institutions: Florida Institute of Technology, University of California, San Francisco

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: National Institute of Biomedical Imaging and Bioengineering

Award: Energy-Independent Single Photon Molecular Imaging Technology