Design patterns in medical imaging information systems

Kent Soo Hoo, Stephen T. Wong, Kenneth D. Laxer, Robert C. Knowlton, Wan Ching

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

The purpose of this paper is to introduce a new and important conceptual framework of software design for the medical imaging community using design patterns. Use cases are created to summarize operational scenarios of clinicians using the system to complete certain tasks such as image segmentation. During design the Unified Modeling Language is used to translate the use cases into modeling diagrams that describe how the system functions. Next, design patterns are applied to build models that describe how software components interoperate to deliver that functionality. The software components are implemented using the Java language, CORBA architecture, and other web technologies. The biomedical image information system is used in epilepsy neurosurgical planning and diagnosis. This article proposes the use of proven software design models for solving medical imaging informatics design problems. Design patterns provide an excellent vehicle to leverage design solutions that have worked in the past to solve the problems we face in building user-friendly, reliable, and efficient information systems. This work introduces this new technology for building increasing complex medical image information systems. The rigorous application of software design techniques is essential in building information systems that are easy to use, rich in functionality, maintainable, reliable, and updateable.

Original languageEnglish (US)
Pages (from-to)256-263
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3980
StatePublished - Jan 1 2000
EventMedical Imaging 2000 - PACS Design and Evaluation: Engineering and Clinical Issues - San Diego, CA, USA
Duration: Feb 15 2000Feb 17 2000

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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