Combined semantic and similarity search in medical image databases

Sascha Seifert; Marisa Thoma; Florian Stegmaier; Matthias Hammon; Martin Kramer; Martin Huber; Hans-Peter Kriegel; Alexander Cavallaro; Dorin Comaniciu

doi:10.1117/12.878179

25 February 2011 Combined semantic and similarity search in medical image databases

Sascha Seifert, Marisa Thoma, Florian Stegmaier, Matthias Hammon, Martin Kramer, Martin Huber, Hans-Peter Kriegel, Alexander Cavallaro, Dorin Comaniciu

Author Affiliations +

Proceedings Volume 7967, Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications; 796703 (2011) https://doi.org/10.1117/12.878179
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

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.

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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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