rdf:type |
|
lifeskim:mentions |
|
pubmed:issue |
1
|
pubmed:dateCreated |
2006-1-9
|
pubmed:abstractText |
We performed neural network clustering on dynamic contrast-enhanced perfusion magnetic resonance imaging time-series in patients with and without stroke. Minimal-free-energy vector quantization, self-organizing maps, and fuzzy c-means clustering enabled self-organized data-driven segmentation with respect to fine-grained differences of signal amplitude and dynamics, thus identifying asymmetries and local abnormalities of brain perfusion. We conclude that clustering is a useful extension to conventional perfusion parameter maps.
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pubmed:language |
eng
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pubmed:journal |
|
pubmed:citationSubset |
IM
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pubmed:chemical |
|
pubmed:status |
MEDLINE
|
pubmed:month |
Jan
|
pubmed:issn |
0278-0062
|
pubmed:author |
|
pubmed:issnType |
Print
|
pubmed:volume |
25
|
pubmed:owner |
NLM
|
pubmed:authorsComplete |
Y
|
pubmed:pagination |
62-73
|
pubmed:dateRevised |
2007-11-15
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pubmed:meshHeading |
pubmed-meshheading:16398415-Algorithms,
pubmed-meshheading:16398415-Artificial Intelligence,
pubmed-meshheading:16398415-Brain,
pubmed-meshheading:16398415-Brain Mapping,
pubmed-meshheading:16398415-Cerebrovascular Circulation,
pubmed-meshheading:16398415-Cluster Analysis,
pubmed-meshheading:16398415-Contrast Media,
pubmed-meshheading:16398415-Echo-Planar Imaging,
pubmed-meshheading:16398415-Humans,
pubmed-meshheading:16398415-Image Enhancement,
pubmed-meshheading:16398415-Image Interpretation, Computer-Assisted,
pubmed-meshheading:16398415-Imaging, Three-Dimensional,
pubmed-meshheading:16398415-Information Storage and Retrieval,
pubmed-meshheading:16398415-Pattern Recognition, Automated,
pubmed-meshheading:16398415-Reproducibility of Results,
pubmed-meshheading:16398415-Sensitivity and Specificity,
pubmed-meshheading:16398415-Stroke,
pubmed-meshheading:16398415-Time Factors
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pubmed:year |
2006
|
pubmed:articleTitle |
Cluster analysis of dynamic cerebral contrast-enhanced perfusion MRI time-series.
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pubmed:affiliation |
Department of Electrical and Computer Engineering, Florida State University, Tallahassee, FL 32310-6046, USA.
|
pubmed:publicationType |
Journal Article,
Clinical Trial
|