Content-based image retrieval in medical applications for picture archiving and communication systems

Thomas Martin Lehmann; Mark Oliver Guld; Christian Thies; Benedikt Fischer; Daniel Keysers; Michael Kohnen; Henning Schubert; Berthold B. Wein

doi:10.1117/12.481942

19 May 2003 Content-based image retrieval in medical applications for picture archiving and communication systems

Thomas Martin Lehmann, Mark Oliver Guld, Christian Thies, Benedikt Fischer, Daniel Keysers, Michael Kohnen, Henning Schubert, Berthold B. Wein

Author Affiliations +

Proceedings Volume 5033, Medical Imaging 2003: PACS and Integrated Medical Information Systems: Design and Evaluation; (2003) https://doi.org/10.1117/12.481942
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

Picture archiving and communication systems (PACS) aim to efficiently provide the radiologists with all images in a suitable quality for diagnosis. Modern standards for digital imaging and communication in medicine (DICOM) comprise alphanumerical descriptions of study, patient, and technical parameters. Currently, this is the only information used to select relevant images within PACS. Since textual descriptions insufficiently describe the great variety of details in medical images, content-based image retrieval (CBIR) is expected to have a strong impact when integrated into PACS. However, existing CBIR approaches usually are limited to a distinct modality, organ, or diagnostic study. In this state-of-the-art report, we present first results implementing a general approach to content-based image retrieval in medical applications (IRMA) and discuss its integration into PACS environments. Usually, a PACS consists of a DICOM image server and several DICOM-compliant workstations, which are used by radiologists for reading the images and reporting the findings. Basic IRMA components are the relational database, the scheduler, and the web server, which all may be installed on the DICOM image server, and the IRMA daemons running on distributed machines, e.g., the radiologists’ workstations. These workstations can also host the web-based front-ends of IRMA applications. Integrating CBIR and PACS, a special focus is put on (a) location and access transparency for data, methods, and experiments, (b) replication transparency for methods in development, (c) concurrency transparency for job processing and feature extraction, (d) system transparency at method implementation time, and (e) job distribution transparency when issuing a query. Transparent integration will have a certain impact on diagnostic quality supporting both evidence-based medicine and case-based reasoning.

Citation Download Citation

Thomas Martin Lehmann, Mark Oliver Guld, Christian Thies, Benedikt Fischer, Daniel Keysers, Michael Kohnen, Henning Schubert, and Berthold B. Wein "Content-based image retrieval in medical applications for picture archiving and communication systems", Proc. SPIE 5033, Medical Imaging 2003: PACS and Integrated Medical Information Systems: Design and Evaluation, (19 May 2003); https://doi.org/10.1117/12.481942

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