title: Design of a large network for radiological image data.
abstract: Radiological imaging is a rapidly growing business. The field is quickly evolving from films to electronic or digital imaging. By the year 2015, the amount of radiological image data that will have been generated in the U.S. alone is projected to be between 100 and 300 000 PB. (1 PB equals 2(50) B or about 10(15) B.) As the volume of radiological data increases, the need to transmit the data over long distances also increases. For example, radiologists in Chicago, India, or Israel, working in the same medical practice, may read images taken in Chicago. Globally distributed research requires that images be transmitted around the world. Radiologists and researchers want to be able to download files containing hundreds of megabytes in seconds. This service requirement suggests that multiple copies of images should be retained in globally distributed databases to minimize access and transmission delays. Key design issues for such a database include the location of the data repositories relative to the generating and retrieval (reading) sites and the number and location of the copies of the files that are generated. In this paper, we approximate the time to retrieve images stored in city j by a radiologist in city k at time period t. Next, we formulate a model designed to minimize the average retrieval time weighted over all demands. We briefly outline a nested Lagrangian relaxation approach to the problem. Computational results are then summarized. The paper ends with conclusion and directions for future research.
authors.affiliation: Sandia National Laboratories, Livermore, CA 94551, USA. marisa.ruffolo@alumni.northwestern.edu
authors.forename: Marisa
authors.initials: M
authors.lastname: Ruffolo
authors.forename: Mark S
authors.initials: MS
authors.lastname: Daskin
authors.forename: Alan V
authors.initials: AV
authors.lastname: Sahakian
authors.forename: Randall A
authors.initials: RA
authors.lastname: Berry
mesh_terms: D003195:Computer Communication Networks / Q000295:instrumentation*; D003628:Database Management Systems / Q000639:trends*; D020000:Decision Support Systems, Clinical; D003952:Diagnostic Imaging / Q000295:instrumentation; D004867:Equipment Design; D019544:Equipment Failure Analysis; D016247:Information Storage and Retrieval / Q000379:methods*; D016347:Medical Records Systems, Computerized / Q000639:trends*; D011873:Radiology Information Systems / Q000295:instrumentation*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D019112:Teleradiology / Q000295:instrumentation* / Q000379:methods; D014481:United States