Creating New Medical Ontologies for Image Annotation [electronic resource] : A Case Study / by Liana Stanescu, Dumitru Dan Burdescu, Marius Brezovan, Cristian Gabriel Mihai.

By: Stanescu, Liana [author.]Contributor(s): Burdescu, Dumitru Dan [author.] | Brezovan, Marius [author.] | Mihai, Cristian Gabriel [author.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: SpringerBriefs in Electrical and Computer Engineering: Publisher: New York, NY : Springer New York : Imprint: Springer, 2012Description: VIII, 111p. 27 illus., 10 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781461419099Subject(s): Engineering | Radiology, Medical | Computer software | Computer vision | Engineering | Signal, Image and Speech Processing | Imaging / Radiology | Image Processing and Computer Vision | Algorithm Analysis and Problem ComplexityAdditional physical formats: Printed edition:: No titleDDC classification: 621.382 LOC classification: TK5102.9TA1637-1638TK7882.S65Online resources: Click here to access online
Contents:
Content Based Image Retrieval in Medical Images Databases -- Medical Images Segmentation -- Ontologies -- Medical Images Annotation -- Semantic Based Image Retrieval -- Object Oriented Medical Annotation System.
In: Springer eBooksSummary: 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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Content Based Image Retrieval in Medical Images Databases -- Medical Images Segmentation -- Ontologies -- Medical Images Annotation -- Semantic Based Image Retrieval -- Object Oriented Medical Annotation System.

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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