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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
1
|
| pubmed:dateCreated |
1985-1-15
|
| pubmed:abstractText |
Magnetic resonance (MR) imaging systems produce spatial distribution estimates of proton density, relaxation time, and flow, in a two dimensional matrix form that is analogous to that of the image data obtained from multispectral imaging satellites. Advanced NASA satellite image processing offers sophisticated multispectral analysis of MR images. Spin echo and inversion recovery pulse sequence images were entered in a digital format compatible with satellite images and accurately registered pixel by pixel. Signatures of each tissue class were automatically determined using both supervised and unsupervised classification. Overall tissue classification was obtained in the form of a theme map. In MR images of the brain, for example, the classes included CSF, gray matter, white matter, subcutaneous fat, muscle, and bone. These methods provide an efficient means of identifying subtle relationships in a multi-image MR study.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
AIM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
Jan
|
| pubmed:issn |
0033-8419
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
154
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
221-4
|
| pubmed:dateRevised |
2004-11-17
|
| pubmed:meshHeading | |
| pubmed:year |
1985
|
| pubmed:articleTitle |
Multispectral analysis of magnetic resonance images.
|
| pubmed:publicationType |
Journal Article
|