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Proceedings Paper

Combined semantic and similarity search in medical image databases
Author(s): Sascha Seifert; Marisa Thoma; Florian Stegmaier; Matthias Hammon; Martin Kramer; Martin Huber; Hans-Peter Kriegel; Alexander Cavallaro; Dorin Comaniciu
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Paper Abstract

The current diagnostic process at hospitals is mainly based on reviewing and comparing images coming from multiple time points and modalities in order to monitor disease progression over a period of time. However, for ambiguous cases the radiologist deeply relies on reference literature or second opinion. Although there is a vast amount of acquired images stored in PACS systems which could be reused for decision support, these data sets suffer from weak search capabilities. Thus, we present a search methodology which enables the physician to fulfill intelligent search scenarios on medical image databases combining ontology-based semantic and appearance-based similarity search. It enabled the elimination of 12% of the top ten hits which would arise without taking the semantic context into account.

Paper Details

Date Published: 25 February 2011
PDF: 10 pages
Proc. SPIE 7967, Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 796703 (25 February 2011); doi: 10.1117/12.878179
Show Author Affiliations
Sascha Seifert, Siemens AG (Germany)
Marisa Thoma, Ludwig-Maximilians-Univ. München (Germany)
Florian Stegmaier, Passau Univ. (Germany)
Matthias Hammon, Univ. Hospital Erlangen (Germany)
Martin Kramer, Siemens AG (Germany)
Martin Huber, Siemens Healthcare (Germany)
Hans-Peter Kriegel, Ludwig-Maximilians-Univ. München (Germany)
Alexander Cavallaro, Univ. Hospital Erlangen (Germany)
Dorin Comaniciu, Siemens Corporate Research (Germany)

Published in SPIE Proceedings Vol. 7967:
Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications
William W. Boonn M.D.; Brent J. Liu, Editor(s)

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