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Information Systems Frontiers

, Volume 11, Issue 4, pp 369–379 | Cite as

Automating object-oriented integration and visualization of multidisciplinary biomedical data in radiology workflow: Compartmental PACS model

  • Alex K. S. Wong
  • Lawrence W. C. ChanEmail author
  • Ying Liu
Article

Abstract

This paper is aimed to present a novel compartmental PACS model for the automatic object-oriented integration and visualization of heterogeneous data for the multidisciplinary biomedical studies in the midst of the imaging services in radiology department. The generic PACS is conceptually partitioned into two compartments: service and integration. The service compartment supports the routine imaging service by connecting the imaging modalities to the web client workstations through a single fault-tolerant hardware. The integration compartment is synthesized by open source and open standard software tools to perform the long-term archiving of imaging cases and to integrate the images with the related data from other clinical disciplines. The prototype of the compartmental PACS model has been successfully implemented in the Department of Health Technology and Informatics (HTI) at the Hong Kong Polytechnic University (PolyU). Multi-disciplinary study on a cardiovascular case is considered as an example in this paper to demonstrate the seamless integration and web-based visualization of heterogeneous data from radiology, ophthalmology, cardiology and hematology. The implementation of the compartmental PACS model demonstrates a deliberative system design for allocating mission-critical components at the clinical frontline of imaging services and long-term archiving components at the backend. The integrative feature of object-oriented long-term archive addresses the comprehensive needs of patient-centered multidisciplinary biomedical studies.

Keywords

Multidisciplinary communication Picture archiving and communications systems Digital imaging and communications in medicine Patient-centered care 

Notes

Acknowledgment

We would like to thank for the donation of RamSoft software license from INQGEN Limited to this research study. This research is supported by the Internal Fund of PolyU “1-ZV39: PACS-based Intelligent Risk Assessment of Diabetic Complications.”

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Alex K. S. Wong
    • 1
  • Lawrence W. C. Chan
    • 1
    Email author
  • Ying Liu
    • 2
  1. 1.Department of Health Technology and InformaticsHong Kong Polytechnic UniversityHung HomPeople’s Republic of China
  2. 2.Department of Industrial and Systems EngineeringHong Kong Polytechnic UniversityHung HomPeople’s Republic of China

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