Creating New Medical Ontologies for Image Annotation : A Case Study

Liana Stanescu, Cristian Gabriel Mihai, Marius Brezovan, Dumitru Dan Burdescu

ISBN 10: 1461419085 / ISBN 13: 9781461419082

Published by Springer New York, 2011

About this Item

Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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.

Seller Inventory # 11234134/12

Bibliographic Details

• Title: Creating New Medical Ontologies for Image Annotation : A Case Study
• Publisher: Springer New York
• Publication Date: 2011
• Language: English
• ISBN 10: 1461419085
• ISBN 13: 9781461419082
• Binding: Soft cover
• Condition: Sehr gut
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.