Source:http://linkedlifedata.com/resource/pubmed/id/16860588
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
5
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| pubmed:dateCreated |
2006-9-4
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| pubmed:abstractText |
An approach to the deformable registration of three-dimensional brain tumor images to a normal brain atlas is presented. The approach involves the integration of three components: a biomechanical model of tumor mass-effect, a statistical approach to estimate the model's parameters, and a deformable image registration method. Statistical properties of the sought deformation map from the atlas to the image of a tumor patient are first obtained through tumor mass-effect simulations on normal brain images. This map is decomposed into the sum of two components in orthogonal subspaces, one representing inter-individual differences in brain shape, and the other representing tumor-induced deformation. For a new tumor case, a partial observation of the sought deformation map is obtained via deformable image registration and is decomposed into the aforementioned spaces in order to estimate the mass-effect model parameters. Using this estimate, a simulation of tumor mass-effect is performed on the atlas image in order to generate an image that is similar to tumor patient's image, thereby facilitating the atlas registration process. Results for a real tumor case and a number of simulated tumor cases indicate significant reduction in the registration error due to the presented approach as compared to the direct use of deformable image registration.
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| pubmed:grant | |
| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:status |
MEDLINE
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| pubmed:month |
Oct
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| pubmed:issn |
1361-8415
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
10
|
| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
752-63
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| pubmed:dateRevised |
2007-12-3
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| pubmed:meshHeading |
pubmed-meshheading:16860588-Algorithms,
pubmed-meshheading:16860588-Artificial Intelligence,
pubmed-meshheading:16860588-Brain Neoplasms,
pubmed-meshheading:16860588-Computer Simulation,
pubmed-meshheading:16860588-Humans,
pubmed-meshheading:16860588-Image Enhancement,
pubmed-meshheading:16860588-Image Interpretation, Computer-Assisted,
pubmed-meshheading:16860588-Imaging, Three-Dimensional,
pubmed-meshheading:16860588-Information Storage and Retrieval,
pubmed-meshheading:16860588-Magnetic Resonance Imaging,
pubmed-meshheading:16860588-Models, Neurological,
pubmed-meshheading:16860588-Models, Statistical,
pubmed-meshheading:16860588-Pattern Recognition, Automated,
pubmed-meshheading:16860588-Reproducibility of Results,
pubmed-meshheading:16860588-Sensitivity and Specificity,
pubmed-meshheading:16860588-Subtraction Technique
|
| pubmed:year |
2006
|
| pubmed:articleTitle |
Deformable registration of brain tumor images via a statistical model of tumor-induced deformation.
|
| pubmed:affiliation |
Section of Biomedical Image Analysis, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. ashraf.mohamed@siemens.com
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| pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, Non-P.H.S.,
Evaluation Studies,
Research Support, N.I.H., Extramural
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