Linked Life Data

19217067

Source:http://linkedlifedata.com/resource/pubmed/id/19217067

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2009-3-3
pubmed:abstractText
The increasing complexity of human body models enabled by advances in diagnostic imaging, computing, and growing knowledge calls for the development of a new generation of systems for intelligent exploration of these models. Here, we introduce a novel paradigm for the exploration of digital body models illustrating cerebral vasculature. It enables dynamic scene compositing, real-time interaction combined with animation, correlation of 3D models with sectional images, quantification as well as 3D manipulation-independent labeling and knowledge-related meta labeling (with name, diameter, description, variants, and references). This novel exploration is incorporated into a 3D atlas of cerebral vasculature with arteries and veins along with the surrounding surface and sectional neuroanatomy derived from 3.0 Tesla scans. This exploration paradigm is useful in medical education, training, research, and clinical applications. It enables development of new generation systems for rapid and intelligent exploration of complicated digital body models in real time with dynamic scene compositing from highly parcellated 3D models, continuous navigation, and manipulation-independent labeling with multiple features.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1935-9780
pubmed:author
pubmed:copyrightInfo
(c) 2009 American Association of Anatomists
pubmed:issnType
Electronic
pubmed:volume
2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
24-33
pubmed:dateRevised
2010-9-30
pubmed:meshHeading
pubmed:articleTitle
A new presentation and exploration of human cerebral vasculature correlated with surface and sectional neuroanatomy.
pubmed:affiliation
Biomedical Imaging Lab, Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 30 Biopolis Street, #07-01 Matrix, Singapore. wieslaw@sbic.a-star.edu.sg
pubmed:publicationType
Journal Article