Creating New Medical Ontologies for Image Annotation

A Case Study

Nonfiction, Health & Well Being, Medical, Medical Science, Biochemistry, Science & Nature, Technology, Electronics
Cover of the book Creating New Medical Ontologies for Image Annotation by Liana Stanescu, Dumitru Dan Burdescu, Marius Brezovan, Cristian Gabriel Mihai, Springer New York
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Author: Liana Stanescu, Dumitru Dan Burdescu, Marius Brezovan, Cristian Gabriel Mihai ISBN: 9781461419099
Publisher: Springer New York Publication: December 16, 2011
Imprint: Springer Language: English
Author: Liana Stanescu, Dumitru Dan Burdescu, Marius Brezovan, Cristian Gabriel Mihai
ISBN: 9781461419099
Publisher: Springer New York
Publication: December 16, 2011
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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