Linked Life Data

21995017

Source:http://linkedlifedata.com/resource/pubmed/id/21995017

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
Pt 2
pubmed:dateCreated
2011-10-14
pubmed:abstractText
We derive herein first and second-order differential operators for detecting structure in diffusion tensor MRI (DTI). Unlike existing methods, we are able to generate full first and second-order differentials without dimensionality reduction and while respecting the underlying manifold of the data. Further, we extend corner and curvature feature detectors to DTI using our differential operators. Results using the feature detectors on diffusion tensor MR images show the ability to highlight structure within the image that existing methods cannot.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:author
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
90-7
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Detecting structure in diffusion tensor MR images.
pubmed:affiliation
Biomedical Signal and Image Computing Lab, University of British Columbia. kkrishna@ece.ubc.ca
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't