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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
3
|
| pubmed:dateCreated |
1993-6-17
|
| pubmed:abstractText |
We present techniques of automatic nonlinear transformation of MR images (2D or 3D). A neural network automatically finds the corresponding parts between the subject's brain images and the standard images. By iterative operations, the network generates a set of image-shifting vectors to realize a plastic transformation. For precise matching, a set of markers can be placed manually before starting the transformation on landmarks of the images, e.g., on the anterior-posterior commissural line and on the central sulcus.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:issn |
0363-8715
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
17
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
455-60
|
| pubmed:dateRevised |
2004-11-17
|
| pubmed:meshHeading |
pubmed-meshheading:8491911-Brain Mapping,
pubmed-meshheading:8491911-Humans,
pubmed-meshheading:8491911-Image Processing, Computer-Assisted,
pubmed-meshheading:8491911-Magnetic Resonance Imaging,
pubmed-meshheading:8491911-Neural Networks (Computer),
pubmed-meshheading:8491911-Stereotaxic Techniques
|
| pubmed:articleTitle |
Neural network mapping for nonlinear stereotactic normalization of brain MR images.
|
| pubmed:affiliation |
Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Japan.
|
| pubmed:publicationType |
Journal Article
|