Combined Semantic and Similarity Search in Medical Image Databases

被引：1

作者：

Seifert, Sascha ^{[1
]}

Thoma, Marisa ^{[2
]}

Stegmaier, Florian ^{[3
]}

Hammon, Matthias ^{[4
]}

Kramer, Martin ^{[1
]}

Huber, Martin ^{[5
]}

Kriegel, Hans-Peter ^{[2
]}

Cavallaro, Alexander ^{[4
]}

Comaniciu, Dorin ^{[6
]}

机构：

[1] Siemens Corp Technology, Erlangen, Germany

[2] Univ Munich, Database Syst Grp, Munich, Germany

[3] Passau Univ, Distributed Informat Syst, Passau, Germany

[4] Univ Hosp Erlangen, Erlangen, Germany

[5] Siemens Healthcare, Erlangen, Germany

[6] Siemens Corp Res, Princeton, NJ USA

来源：

MEDICAL IMAGING 2011: ADVANCED PACS-BASED IMAGING INFORMATICS AND THERAPEUTIC APPLICATIONS | 2011年 / 7967卷

关键词：

content-based image retrieval; ontological modeling; semantic image annotation; RETRIEVAL;

D O I：

10.1117/12.878179

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

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.

引用

页数：10

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