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Updated: Mar 22, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
Published on: October 27, 2023
Parallelization of Iterative Reconstruction Algorithms in Multiple Modalities
Debasis Mitra1, Hui Pan1, Fares Alhassen2
1Computer Science Department, Florida Institute of Technology, 150 West Univ. Blvd., Melbourne, FL, 32901.
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.

