A parallel Monte Carlo code for planar and SPECT imaging: implementation, verification and applications in (131)I SPECT
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Updated: Oct 2, 2026

Visualization of Low-Level Gamma Radiation Sources Using a Low-Cost, High-Sensitivity, Omnidirectional Compton Camera
Published on: January 30, 2020
Yuni K Dewaraja1, Michael Ljungberg, Amitava Majumdar
1Department of Radiology, Division of Nuclear Medicine, The University of Michigan Medical Center, 3480 Kresge III, 204 Zina Pitcher Place, Ann Arbor, MI 48109-0552, USA. yuni@umich.edu
Abstract:
This paper reports the implementation of the SIMIND Monte Carlo code on an IBM SP2 distributed memory parallel computer. Basic aspects of running Monte Carlo particle transport calculations on parallel architectures are described. Our parallelization is based on equally partitioning photons among the processors and uses the Message Passing Interface (MPI) library for interprocessor communication and the Scalable Parallel Random Number Generator (SPRNG) to generate uncorrelated random number streams. These parallelization techniques are also applicable to other distributed memory architectures. A linear increase in computing speed with the number of processors is demonstrated for up to 32 processors. This speed-up is especially significant in Single Photon Emission Computed Tomography (SPECT) simulations involving higher energy photon emitters, where explicit modeling of the phantom and collimator is required. For (131)I, the accuracy of the parallel code is demonstrated by comparing simulated and experimental SPECT images from a heart/thorax phantom. Clinically realistic SPECT simulations using the voxel-man phantom are carried out to assess scatter and attenuation correction.
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