Image quality in lossy compressed digital mammograms
Signal Processing
Ontology Learning for the Semantic Web
Ontology Learning for the Semantic Web
IASTED-HCI '07 Proceedings of the Second IASTED International Conference on Human Computer Interaction
Semantic annotation for knowledge management: Requirements and a survey of the state of the art
Web Semantics: Science, Services and Agents on the World Wide Web
The MPEG-7 visual standard for content description-an overview
IEEE Transactions on Circuits and Systems for Video Technology
Notes on a Linguistic Description as the Basis for Automatic Image Understanding
International Journal of Applied Mathematics and Computer Science
The role of sparse data representation in semantic image understanding
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part I
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This paper presents the current limitations and challenges of computer-aided interpretation of radiological examinations. The analysis and the proposed improvements in interpretation arose from our experience, knowledge and observations with the collected suggestions and conclusions. The emphasized topics are as follows: computer understanding of human determinants of diagnosis, characteristics and enhancement of observer performance, diagnostic accuracy measures of image examinations, computer-aided diagnosis (CAD) systems, and numerical description of medical image-based content. All of these diagnosis support concepts can be integrated into an intelligent diagnosis interface and enhanced, basing on a formal description of semantic image content, i.e. ontology implied as a reliable, dynamic platform of medical knowledge, useful for diagnosis. CAD for mammography and content-based image indexing supported by the ontology were integrated for the needs of an enhanced diagnostic workstation applied in tele-information medical systems. A design of an effective human-machine interface has arisen as the leading problem of the current challenges.