Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
Proceedings of the 2nd international conference on Knowledge capture
A reference ontology for biomedical informatics: the foundational model of anatomy
Journal of Biomedical Informatics - Special issue: Unified medical language system
Obol: integrating language and meaning in bio-ontologies: Conference Papers
Comparative and Functional Genomics
Just the right amount: extracting modules from ontologies
Proceedings of the 16th international conference on World Wide Web
Semantic Visualization of Patient Information
CBMS '08 Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems
Modular Ontologies
Structure-Based Partitioning of Large Ontologies
Modular Ontologies
RadSem: Semantic Annotation and Retrieval for Medical Images
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
KEMM: A Knowledge Engineering Methodology in the Medical Domain
Proceedings of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008)
Modular Ontologies: Concepts, Theories and Techniques for Knowledge Modularization
Modular Ontologies: Concepts, Theories and Techniques for Knowledge Modularization
Statistical term profiling for query pattern mining
BioNLP '08 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Guest Editorial: Ontologies for clinical and translational research: Introduction
Journal of Biomedical Informatics
Real web community based automatic image annotation
Computers and Electrical Engineering
Medical data management in the SYSEO project
ACM SIGMOD Record
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Searching for medical images and patient reports is a significant challenge in a clinical setting. The contents of such documents are often not described in sufficient detail thus making it difficult to utilize the inherent wealth of information contained within them. Semantic image annotation addresses this problem by describing the contents of images and reports using medical ontologies. Medical images and patient reports are then linked to each other through common annotations. Subsequently, search algorithms can more effectively find related sets of documents on the basis of these semantic descriptions. A prerequisite to realizing such a semantic search engine is that the data contained within should have been previously annotated with concepts from medical ontologies. One major challenge in this regard is the size and complexity of medical ontologies as annotation sources. Manual annotation is particularly time consuming labor intensive in a clinical environment. In this article we propose an approach to reducing the size of clinical ontologies for more efficient manual image and text annotation. More precisely, our goal is to identify smaller fragments of a large anatomy ontology that are relevant for annotating medical images from patients suffering from lymphoma. Our work is in the area of ontology modularization, which is a recent and active field of research. We describe our approach, methods and data set in detail and we discuss our results.