Multicomputer processing for medical imaging

Iain Goddard; Jonathon Greene; Brian Bouzas

doi:10.1117/12.207633

27 April 1995 Multicomputer processing for medical imaging

Iain Goddard, Jonathon Greene, Brian Bouzas

Proceedings Volume 2431, Medical Imaging 1995: Image Display; (1995) https://doi.org/10.1117/12.207633
Event: Medical Imaging 1995, 1995, San Diego, CA, United States

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.

Citation Download Citation

Iain Goddard, Jonathon Greene, and Brian Bouzas "Multicomputer processing for medical imaging", Proc. SPIE 2431, Medical Imaging 1995: Image Display, (27 April 1995); https://doi.org/10.1117/12.207633

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