Linked Life Data

11700739

Source:http://linkedlifedata.com/resource/pubmed/id/11700739

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2001-11-9
pubmed:abstractText
We address the problem of applying spatial transformations (or "image warps") to diffusion tensor magnetic resonance images. The orientational information that these images contain must be handled appropriately when they are transformed spatially during image registration. We present solutions for global transformations of three-dimensional images up to 12-parameter affine complexity and indicate how our methods can be extended for higher order transformations. Several approaches are presented and tested using synthetic data. One method, the preservation of principal direction algorithm, which takes into account shearing, stretching and rigid rotation, is shown to be the most effective. Additional registration experiments are performed on human brain data obtained from a single subject, whose head was imaged in three different orientations within the scanner. All of our methods improve the consistency between registered and target images over naïve warping algorithms.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0278-0062
pubmed:author
pubmed:issnType
Print
pubmed:volume
20
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1131-9
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Spatial transformations of diffusion tensor magnetic resonance images.
pubmed:affiliation
Department of Computer Science, University College London, UK. daniel.alexander@cs.ucl.ac.uk
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S.