Medical image processing and analysis software
Handbook of medical imaging
Foundations of Image Understanding
Foundations of Image Understanding
Indexing the Solution Space: A New Technique for Nearest Neighbor Search in High-Dimensional Space
IEEE Transactions on Knowledge and Data Engineering
Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential
Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential
Semantic video summarization in compressed domain MPEG video
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Modeling people: vision-based understanding of a person's shape, appearance, movement, and behaviour
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
IEEE Internet Computing
Distributed Cross-Modal Search within the MPEG Query Format
WIAMIS '08 Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services
Modern Computational Intelligence Methods for the Interpretation of Medical Images
Modern Computational Intelligence Methods for the Interpretation of Medical Images
Artificial intelligence techniques in retrieval of visual data semantic information
AWIC'03 Proceedings of the 1st international Atlantic web intelligence conference on Advances in web intelligence
Using grammars for pattern recognition in images: A systematic review
ACM Computing Surveys (CSUR)
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The task of carrying out semantic searches for useful information was solved to some degree for textual data. Unfortunately, medical image analysis has demonstrated that the issue of searching for useful semantic information, on the basis of content, is an insolvable task, in practice. We have acquired a certain expertise in using automatic techniques for retrieving features that define the semantic content of visual data. Everything seems to suggest that the techniques of syntactic pattern analysis which are useful in computer-aided medical diagnosis can also be very helpful in tasks involving automatic understanding procedures used in medical image interpretation systems.Therefore, the topic of this paper will be the presentation of application possibilities for graph EDT grammars as well as context-free grammars as cognitive techniques supporting medical pattern semantic interpretation. Those mathematical linguistic mechanisms will be used for the automatic generation of syntactic descriptions of the contents of the analyzed types of medical images originating from pancreas ERCP examinations, spinal cord visualization and wrist radiograms. The semantics of those patterns define the type of incorrectness of the organ shown on it. Attention will be focused on the methods of cognitive analysis with respect to medical data. So, the languages of shape description and proposed grammars mainly allow for the creation of syntactic descriptions of selected anatomic organs together with a definition of the semantic meaning of the changes in their shapes. Such descriptions will allow us to create a semantically-oriented representation of visual data describing pattern features which are useful in medical decisions and computer-aided diagnostic systems.