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

Authors:
Alex K. Wong;Lawrence W. Chan;Ying Liu
Affiliations:
Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hung Hom, People's Republic of China;Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hung Hom, People's Republic of China;Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hung Hom, People's Republic of China
Venue:
Information Systems Frontiers
Year:
2009

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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.