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01000naa a22002652 4500 |
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NLM098644637 |
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DE-627 |
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20231222112458.0 |
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tu |
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231222s1998 xx ||||| 00| ||eng c |
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|a eng
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| 100 |
1 |
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|a Lowe, H J
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Towards knowledge-based retrieval of medical images. The role of semantic indexing, image content representation and knowledge-based retrieval
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| 264 |
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1 |
|c 1998
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| 336 |
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|a Text
|b txt
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|a ohne Hilfsmittel zu benutzen
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|2 rdamedia
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|b nc
|2 rdacarrier
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|a Date Completed 16.03.1999
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| 500 |
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|a Date Revised 10.12.2019
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| 500 |
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|a published: Print
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| 500 |
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|a Citation Status MEDLINE
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| 520 |
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|a Medicine is increasingly image-intensive. The central importance of imaging technologies such as computerized tomography and magnetic resonance imaging in clinical decision making, combined with the trend to store many "traditional" clinical images such as conventional radiographs, microscopic pathology and dermatology images in digital format present both challenges and an opportunities for the designers of clinical information systems. The emergence of Multimedia Electronic Medical Record Systems (MEMRS), architectures that integrate medical images with text-based clinical data, will further hasten this trend. The development of these systems, storing a large and diverse set of medical images, suggests that in the future MEMRS will become important digital libraries supporting patient care, research and education. The representation and retrieval of clinical images within these systems is problematic as conventional database architectures and information retrieval models have, until recently, focused largely on text-based data. Medical imaging data differs in many ways from text-based medical data but perhaps the most important difference is that the information contained within imaging data is fundamentally knowledge-based. New representational and retrieval models for clinical images will be required to address this issue. Within the Image Engine multimedia medical record system project at the University of Pittsburgh we are evolving an approach to representation and retrieval of medical images which combines semantic indexing using the UMLS Metathesuarus, image content-based representation and knowledge-based image analysis
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| 650 |
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|a Journal Article
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| 650 |
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4 |
|a Research Support, U.S. Gov't, P.H.S.
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| 700 |
1 |
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|a Antipov, I
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Hersh, W
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Smith, C A
|e verfasserin
|4 aut
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|i Enthalten in
|t Proceedings. AMIA Symposium
|d 1998
|g (1998) vom: 13., Seite 882-6
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