Interactive volume rendering on a multicomputer
I3D '92 Proceedings of the 1992 symposium on Interactive 3D graphics
Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering
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Performances of the PS2 Parallel Storage and Processing System for Tomographic Image
ICPADS '97 Proceedings of the 1997 International Conference on Parallel and Distributed Systems
Fast Processing of Medical Images Using a New Parallel Architecture, the Hybrid System
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
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Maximum likelihood (ML) estimation is used during tomosynthesis mammography reconstruction. A single reconstruction involves the processing of highresolution projection images, which is both computeintensive and time-consuming. This workload is presently a bottleneck in the accurate diagnosis of breast cancer during screening. This paper presents our parallelization work on an ML algorithm using three different partitioning models: no inter-communication, overlap with inter-communication and non-overlap model. These models are evaluated to obtain the best reconstruction performance given a range of computing environments with different computational power and network speed. Our test results show that the non-overlap method outperforms the other two methods on all five computing platforms evaluated. This parallelization of ML has enabled tomosynthesis to become a viable technology in the breast screening clinic, reducing reconstruction time from 3 hours on a PentiumIV workstation to 6 minutes on a 32-node PentiumIV cluster.