Literature DB >> 22254818

A semantically-aided approach for online annotation and retrieval of medical images.

George K Kyriazos1, Ilias Th Gerostathopoulos, Vassileios D Kolias, John S Stoitsis, Konstantina S Nikita.   

Abstract

The need for annotating the continuously increasing volume of medical image data is recognized from medical experts for a variety of purposes, regardless if this is medical practice, research or education. The rich information content latent in medical images can be made explicit and formal with the use of well-defined ontologies. Evolution of the Semantic Web now offers a unique opportunity of a web-based, service-oriented approach. Remote access to FMA and ICD-10 reference ontologies provides the ontological annotation framework. The proposed system utilizes this infrastructure to provide a customizable and robust annotation procedure. It also provides an intelligent search mechanism indicating the advantages of semantic over keyword search. The common representation layer discussed facilitates interoperability between institutions and systems, while semantic content enables inference and knowledge integration.

Mesh:

Year:  2011        PMID: 22254818     DOI: 10.1109/IEMBS.2011.6090662

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  1 in total

1.  [Automatic segmentation and annotation in radiology].

Authors:  P Dankerl; A Cavallaro; M Uder; M Hammon
Journal:  Radiologe       Date:  2014-03       Impact factor: 0.635

  1 in total

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