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Creating New Medical Ontologies for Image Annotation: A Case Study

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 algorithm...

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Detalles Bibliográficos
Autores principales: Stanescu, Liana, Burdescu, Dumitru Dan, Brezovan, Marius, Mihai, Cristian Gabriel
Lenguaje:eng
Publicado: Springer 2012
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-1-4614-1909-9
http://cds.cern.ch/record/1503762
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author Stanescu, Liana
Burdescu, Dumitru Dan
Brezovan, Marius
Mihai, Cristian Gabriel
author_facet Stanescu, Liana
Burdescu, Dumitru Dan
Brezovan, Marius
Mihai, Cristian Gabriel
author_sort Stanescu, Liana
collection CERN
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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spelling cern-15037622021-04-21T23:53:32Zdoi:10.1007/978-1-4614-1909-9http://cds.cern.ch/record/1503762engStanescu, LianaBurdescu, Dumitru DanBrezovan, MariusMihai, Cristian GabrielCreating New Medical Ontologies for Image Annotation: A Case StudyEngineeringCreating 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.Springeroai:cds.cern.ch:15037622012
spellingShingle Engineering
Stanescu, Liana
Burdescu, Dumitru Dan
Brezovan, Marius
Mihai, Cristian Gabriel
Creating New Medical Ontologies for Image Annotation: A Case Study
title Creating New Medical Ontologies for Image Annotation: A Case Study
title_full Creating New Medical Ontologies for Image Annotation: A Case Study
title_fullStr Creating New Medical Ontologies for Image Annotation: A Case Study
title_full_unstemmed Creating New Medical Ontologies for Image Annotation: A Case Study
title_short Creating New Medical Ontologies for Image Annotation: A Case Study
title_sort creating new medical ontologies for image annotation: a case study
topic Engineering
url https://dx.doi.org/10.1007/978-1-4614-1909-9
http://cds.cern.ch/record/1503762
work_keys_str_mv AT stanesculiana creatingnewmedicalontologiesforimageannotationacasestudy
AT burdescudumitrudan creatingnewmedicalontologiesforimageannotationacasestudy
AT brezovanmarius creatingnewmedicalontologiesforimageannotationacasestudy
AT mihaicristiangabriel creatingnewmedicalontologiesforimageannotationacasestudy