27 April 1995 Multicomputer processing for medical imaging
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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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Iain Goddard, Jonathon Greene, Brian Bouzas, "Multicomputer processing for medical imaging", Proc. SPIE 2431, Medical Imaging 1995: Image Display, (27 April 1995); doi: 10.1117/12.207633; https://doi.org/10.1117/12.207633
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