Linked Life Data

20426068

Source:http://linkedlifedata.com/resource/pubmed/id/20426068

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PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
Pt 1
pubmed:dateCreated
2010-4-29
pubmed:abstractText
We present a method for the fully automated extraction of the cingulum using diffusion tensor imaging (DTI) data. We perform whole-brain tractography and initialize tract selection in the cingulum with a registered DTI atlas. Tracts are parameterized from which tract co-linearity is derived. The tract set, filtered on the basis of co-linearity with the cingulum shape, yields an improved segmentation of the cingulum and is subsequently optimized in an iterative fashion to further improve the tract selection. We evaluate the method using a large DTI database of 500 subjects from the general population and show robust extraction of tracts in the entire cingulate bundle in both hemispheres. We demonstrate the use of the extracted fiber-tracts to compare left and right cingulate bundles. Our asymmetry analysis shows a higher fractional anisotropy in the left anterior part of the cingulum compared to the right side, and the opposite effect in the posterior part.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:author
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
853-60
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Iterative co-linearity filtering and parameterization of fiber tracts in the entire cingulum.
pubmed:affiliation
Biomedical Imaging Group Rotterdam, Department of Radiology, Erasmus MC, Rotterdam, The Netherlands. marius.degroot@erasmusmc.nl
pubmed:publicationType
Journal Article