title: Parallelization of Iterative Reconstruction Algorithms in Multiple Modalities.
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.
authors.affiliation: Computer Science Department, Florida Institute of Technology, 150 West Univ. Blvd., Melbourne, FL, 32901.
authors.forename: Debasis
authors.initials: D
authors.lastname: Mitra
authors.affiliation: Computer Science Department, Florida Institute of Technology, 150 West Univ. Blvd., Melbourne, FL, 32901.
authors.forename: Hui
authors.initials: H
authors.lastname: Pan
authors.affiliation: UCSF Physics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco.
authors.forename: Fares
authors.initials: F
authors.lastname: Alhassen
authors.affiliation: UCSF Physics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco.
authors.forename: Youngho
authors.initials: Y
authors.lastname: Seo