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25 February 2011 Combined semantic and similarity search in medical image databases
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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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sascha Seifert, Marisa Thoma, Florian Stegmaier, Matthias Hammon, Martin Kramer, Martin Huber, Hans-Peter Kriegel, Alexander Cavallaro, and Dorin Comaniciu "Combined semantic and similarity search in medical image databases", Proc. SPIE 7967, Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 796703 (25 February 2011); https://doi.org/10.1117/12.878179
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