Linked Life Data

14568510

Source:http://linkedlifedata.com/resource/pubmed/id/14568510

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2003-10-21
pubmed:abstractText
Functional MRI studies are very sensitive to motion; head movements of as little as 1-mm translations or 1 degrees rotations may cause spurious signals. An algorithm was developed that uses k-space MRI data to monitor subject motion during functional MRI time series. A k-space weighted average of squared difference between the initial scan and subsequent scans is calculated, which summarizes subject motion in a single quality parameter; however, the quality parameter cannot be used for motion correction. The evolution of this quality parameter throughout a time series indicates whether head motion is within a predetermined limit. Fifty functional MRI studies were used to calibrate the sensitivity of the algorithm, using the six rigid-body registration parameters (three translations and three rotations) from the statistical parametric mapping (SPM99) package as a reference. The average correlation coefficient between the new quality parameter and the reference value from SPM was 0.84. The simple algorithm correctly classified acceptable or excessive motion with 90% accuracy, with the remaining 10% being borderline cases. This method makes it possible to evaluate brain motion within seconds after a scan and to decide whether a study needs to be repeated.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1053-8119
pubmed:author
pubmed:issnType
Print
pubmed:volume
20
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1411-8
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
k-Space based summary motion detection for functional magnetic resonance imaging.
pubmed:affiliation
Medical Department, Brookhaven National Laboratory, Upton, NY 11973, USA. caparelli@bnl.gov
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't