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Creating New Medical Ontologies for Image Annotation: A Case Study (2012)

Contributor(s): Stanescu, Liana (Author), Burdescu, Dumitru Dan (Author), Brezovan, Marius (Author), Mihai, Cristian Gabriel (Author)

ISBN: 9781461419082

Publisher: Springer

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Pub Date: December 15, 2011

Dewey: 610.285

LCCN: 2011943747

Lexile Code: 0000

Features: Bibliography, Illustrated

Target Age Group: NA to NA

Physical Info: 0.20" H x 8.80" L x 5.90" W ( 0.25 lbs) 111 pages

Series: Springerbriefs in Electrical and Computer Engineering

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Description: Creating New Medical Ontologies for Image Annotation focuses on the problem of the medical images automatic annotation process, which is solved in an original manner by the authors. All the steps of this process are described in detail with algorithms, experiments and results. The original algorithms proposed by authors are compared with other efficient similar algorithms.

In addition, the authors treat the problem of creating ontologies in an automatic way, starting from Medical Subject Headings (MESH). They have presented some efficient and relevant annotation models and also the basics of the annotation model used by the proposed system: Cross Media Relevance Models. Based on a text query the system will retrieve the images that contain objects described by the keywords.

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