Design of a large network for radiological image data

Marisa Ruffolo*, Mark S. Daskin, Alan V. Sahakian, Randall A. Berry

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Scopus citations

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 250 B or about 1015 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 κ at time period τ. 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.

Original languageEnglish (US)
Pages (from-to)25-39
Number of pages15
JournalIEEE Transactions on Information Technology in Biomedicine
Volume11
Issue number1
DOIs
StatePublished - Jan 1 2007

Keywords

  • Data storage
  • Digital medical imaging
  • Digital medical imaging network
  • Location theory
  • Medical imaging
  • Network design
  • Optimization theory

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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