Linked Life Data

18999144

Source:http://linkedlifedata.com/resource/pubmed/id/18999144

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2008-11-12
pubmed:abstractText
Radiological images contain a wealth of information,such as anatomy and pathology, which is often not explicit and computationally accessible. Information schemes are being developed to describe the semantic content of images, but such schemes can be unwieldy to operationalize because there are few tools to enable users to capture structured information easily as part of the routine research workflow. We have created iPad, an open source tool enabling researchers and clinicians to create semantic annotations on radiological images. iPad hides the complexity of the underlying image annotation information model from users, permitting them to describe images and image regions using a graphical interface that maps their descriptions to structured ontologies semi-automatically. Image annotations are saved in a variety of formats,enabling interoperability among medical records systems, image archives in hospitals, and the Semantic Web. Tools such as iPad can help reduce the burden of collecting structured information from images, and it could ultimately enable researchers and physicians to exploit images on a very large scale and glean the biological and physiological significance of image content.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1942-597X
pubmed:author
pubmed:issnType
Electronic
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
626-30
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
iPad: Semantic annotation and markup of radiological images.
pubmed:affiliation
Center for Biomedical Informatics Research,Stanford Univeristy, CA, USA.
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural