Combined semantic and similarity search in medical image databases
Sascha Seifert, Marisa Thoma, Florian Stegmaier, Matthias Hammon, Martin Krämer, Martin Huber, Hans‐Peter Kriegel, Alexander Cavallaro, Dorin Comaniciu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
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.