Combined semantic and similarity search in medical image databases
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.
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