Paper
3 March 2012 Roadmap for efficient parallelization of breast anatomy simulation
Author Affiliations +
Abstract
A roadmap has been proposed to optimize the simulation of breast anatomy by parallel implementation, in order to reduce the time needed to generate software breast phantoms. The rapid generation of high resolution phantoms is needed to support virtual clinical trials of breast imaging systems. We have recently developed an octree-based recursive partitioning algorithm for breast anatomy simulation. The algorithm has good asymptotic complexity; however, its current MATLAB implementation cannot provide optimal execution times. The proposed roadmap for efficient parallelization includes the following steps: (i) migrate the current code to a C/C++ platform and optimize it for single-threaded implementation; (ii) modify the code to allow for multi-threaded CPU implementation; (iii) identify and migrate the code to a platform designed for multithreaded GPU implementation. In this paper, we describe our results in optimizing the C/C++ code for single-threaded and multi-threaded CPU implementations. As the first step of the proposed roadmap we have identified a bottleneck component in the MATLAB implementation using MATLAB's profiling tool, and created a single threaded CPU implementation of the algorithm using C/C++'s overloaded operators and standard template library. The C/C++ implementation has been compared to the MATLAB version in terms of accuracy and simulation time. A 520-fold reduction of the execution time was observed in a test of phantoms with 50- 400 μm voxels. In addition, we have identified several places in the code which will be modified to allow for the next roadmap milestone of the multithreaded CPU implementation.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joseph H. Chui, David D. Pokrajac, Andrew D. A. Maidment, and Predrag R. Bakic "Roadmap for efficient parallelization of breast anatomy simulation", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83134T (3 March 2012); https://doi.org/10.1117/12.912125
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Cited by 6 scholarly publications.
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KEYWORDS
MATLAB

C++

Breast

Computer simulations

Profiling

Tissues

Algorithm development

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