Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2001-2-22
pubmed:abstractText
In this work, a method for segmenting human brain MR scans on the basis of perfusion is described. This technique uses a measure of similarity between the time-intensity curves obtained with dynamic susceptibility contrast-enhanced MRI and a modeled curve of reference to isolate a tissue of interest, such as white or gray matter. The aim of this study was to validate the method by performing segmentation of white and gray matter in six controls. The relative regional blood volume gray-to-white matter ratio was used as a criterion to assess the quality of segmentation. On average, this ratio was 2.1 +/- 0.2, which is in good agreement with the literature, thus suggesting reliable segmentation. In the case of abnormal perfusion, time-intensity curves are different in shape than that of normal tissue. Therefore, this approach might allow the segmentation of pathological regions, and combined with an indicator-dilution analysis might offer new possibilities for characterizing a brain pathology. Magn Reson Med 45:261-268, 2001.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0740-3194
pubmed:author
pubmed:copyrightInfo
Copyright 2001 Wiley-Liss, Inc.
pubmed:issnType
Print
pubmed:volume
45
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
261-8
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Perfusion-based segmentation of the human brain using similarity mapping.
pubmed:affiliation
CREATIS, CNRS Research Unit (affiliated with INSERM), Lyon, France.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't