Linked Life Data

18302238

Source:http://linkedlifedata.com/resource/pubmed/id/18302238

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2008-4-3
pubmed:abstractText
In breast MRI mammography both high temporal resolution and high spatial resolution have been shown to be important in improving specificity. Adaptive methods such as projection reconstruction time-resolved imaging of contrast kinetics (PR-TRICKS) allow images to be reconstructed at various temporal and spatial resolutions from the same data set. The main disadvantage is that the undersampling, which is necessary to produce high temporal resolution images, leads to the presence of streak artifacts in the images. We present a novel method of removing these artifacts using independent components analysis (ICA) and demonstrate that this results in a significant improvement in image quality for both simulation studies and for patient dynamic contrast-enhanced (DCE)-MRI images. We also investigate the effect of artifacts on two quantitative measures of contrast enhancement. Using simulation studies we demonstrate that streak artifacts lead to pronounced periodic oscillations in pixel concentration curves which, in turn, lead to increased errors and introduce bias into heuristic measurements. ICA filtering significantly reduces this bias and improves accuracy. Pharmacokinetic modeling was more robust and there was no evidence of bias due to the presence of streak artifacts. ICA filtering did not significantly reduce the errors in the estimated pharmacokinetic parameters; however, the chi-squared error was greatly reduced after ICA filtering.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0740-3194
pubmed:author
pubmed:issnType
Print
pubmed:volume
59
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
874-84
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Removing undersampling artifacts in DCE-MRI studies using independent components analysis.
pubmed:affiliation
Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada. anne.martel@sri.utoronto.ca
pubmed:publicationType
Journal Article