Linked Life Data

16300968

Source:http://linkedlifedata.com/resource/pubmed/id/16300968

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2006-3-27
pubmed:abstractText
Longitudinal and multi-site clinical studies create the imperative to characterize and correct technological sources of variance that limit image reproducibility in high-resolution structural MRI studies, thus facilitating precise, quantitative, platform-independent, multi-site evaluation. In this work, we investigated the effects that imaging gradient non-linearity have on reproducibility of multi-site human MRI. We applied an image distortion correction method based on spherical harmonics description of the gradients and verified the accuracy of the method using phantom data. The correction method was then applied to the brain image data from a group of subjects scanned twice at multiple sites having different 1.5 T platforms. Within-site and across-site variability of the image data was assessed by evaluating voxel-based image intensity reproducibility. The image intensity reproducibility of the human brain data was significantly improved with distortion correction, suggesting that this method may offer improved reproducibility in morphometry studies. We provide the source code for the gradient distortion algorithm together with the phantom data.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1053-8119
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
30
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
436-43
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Reliability in multi-site structural MRI studies: effects of gradient non-linearity correction on phantom and human data.
pubmed:affiliation
MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Building 149, 13th Street, Radiology/CNY149-Room 2301, Charlestown, MA 02129, USA. jovicich@nmr.mgh.harvard.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural