Grid enabled magnetic resonance scanners for near real-time medical image processing

Authors:
Jason C. Crane;Forrest W. Crawford;Sarah J. Nelson
Affiliations:
Department of Radiology, University of California, San Francisco, CA 94143-2532, USA;Department of Radiology, University of California, San Francisco, CA 94143-2532, USA;Department of Radiology, University of California, San Francisco, CA 94143-2532, USA
Venue:
Journal of Parallel and Distributed Computing
Year:
2006

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Abstract

This paper presents the initial steps taken to integrate the University of California at San Francisco Radiology Department's magnetic resonance (MR) scanners with its high-performance computing (HPC) grid. The objective is to improve patient care by enabling near real-time, computationally intensive medical image processing, directly at an MR scanner. A graphical software tool is described that was developed to run on the MR scanners for submitting processing jobs to the Departmental grid. The computationally intensive parallel reconstruction and quantification of large, multi-dimensional MR spectroscopic imaging (MRSI) data sets was used as the prototype application for this system. Initial results indicate that real-time processing of medical imaging data on a shared HPC resource is reliable and possible in a clinically acceptable time of less than 5min. The Department's HPC resource is comprised of hardware owned by multiple research groups at three separate University facilities throughout San Francisco.