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Proceedings Paper

Multicomputer processing for medical imaging
Author(s): Iain Goddard; Jonathon Greene; Brian Bouzas
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Paper Abstract

Medical imaging applications have growing processing requirements, and scalable multicomputers are needed to support these applications. Scalability -- performance speedup equal to the increased number of processors -- is necessary for a cost-effective multicomputer. We performed tests of performance and scalability on one through 16 processors on a RACE multicomputer using Parallel Application system (PAS) software. Data transfer and synchronization mechanisms introduced a minimum of overhead to the multicomputer's performance. We implemented magnetic resonance (MR) image reconstruction and multiplanar reformatting (MPR) algorithms, and demonstrated high scalability; the 16- processor configuration was 80% to 90% efficient, and the smaller configurations had higher efficiencies. Our experience is that PAS is a robust and high-productivity tool for developing scalable multicomputer applications.

Paper Details

Date Published: 27 April 1995
PDF: 12 pages
Proc. SPIE 2431, Medical Imaging 1995: Image Display, (27 April 1995); doi: 10.1117/12.207633
Show Author Affiliations
Iain Goddard, Mercury Computer Systems, Inc. (United States)
Jonathon Greene, Mercury Computer Systems, Inc. (United States)
Brian Bouzas, Mercury Computer Systems, Inc. (United States)

Published in SPIE Proceedings Vol. 2431:
Medical Imaging 1995: Image Display
Yongmin Kim, Editor(s)

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