Linked Life Data

20426105

Source:http://linkedlifedata.com/resource/pubmed/id/20426105

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
Pt 2
pubmed:dateCreated
2010-4-29
pubmed:abstractText
Here we propose a novel method to compute Teichmiiller shape space based shape index to study brain morphometry. Such a shape index is intrinsic, and invariant under conformal transformations, rigid motions and scaling. We conformally map a genus-zero open boundary surface to the Poincaré disk with the Yamabe flow method. The shape indices that we compute are the lengths of a special set of geodesics under hyperbolic metric. Tests on longitudinal brain imaging data were used to demonstrate the stability of the derived feature vectors. In leave-one-out validation tests, we achieved 100% accurate classification (versus only 68% accuracy for volume measures) in distinguishing 11 HIV/AIDS individuals from 8 healthy control subjects, based on Teichmüller coordinates for lateral ventricular surfaces extracted from their 3D MRI scans.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:author
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
133-40
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Teichmöller shape space theory and its application to brain morphometry.
pubmed:affiliation
Lab. of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA 90095, USA. ylwang@loni.ucla.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural