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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
1
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pubmed:dateCreated |
2004-1-14
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pubmed:abstractText |
This paper examines an alternative approach to separating magnetic resonance imaging (MRI) intensity inhomogeneity from underlying tissue-intensity structure using a direct template-based paradigm. This permits the explicit spatial modeling of subtle intensity variations present in normal anatomy which may confound common retrospective correction techniques using criteria derived from a global intensity model. A fine-scale entropy driven spatial normalisation procedure is employed to map intensity distorted MR images to a tissue reference template. This allows a direct estimation of the relative bias field between template and subject MR images, from the ratio of their low-pass filtered intensity values. A tissue template for an aging individual is constructed and used to correct distortion in a set of data acquired as part of a study on dementia. A careful validation based on manual segmentation and correction of nine datasets with a range of anatomies and distortion levels is carried out. This reveals a consistent improvement in the removal of global intensity variation in terms of the agreement with a global manual bias estimate, and in the reduction in the coefficient of intensity variation in manually delineated regions of white matter.
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pubmed:grant |
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pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-10600418,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-10860804,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-11304082,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-11304088,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-11305886,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-11445259,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-1545027,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-8843382,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-9448780,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-9469718,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-9754126,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-9873902,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-9873920,
http://linkedlifedata.com/resource/pubmed/commentcorrection/14719691-9931268
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:month |
Jan
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pubmed:issn |
0278-0062
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pubmed:author |
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pubmed:issnType |
Print
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pubmed:volume |
23
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
99-110
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pubmed:dateRevised |
2010-12-3
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pubmed:meshHeading |
pubmed-meshheading:14719691-Aging,
pubmed-meshheading:14719691-Algorithms,
pubmed-meshheading:14719691-Alzheimer Disease,
pubmed-meshheading:14719691-Brain,
pubmed-meshheading:14719691-Computer Simulation,
pubmed-meshheading:14719691-Dementia,
pubmed-meshheading:14719691-Humans,
pubmed-meshheading:14719691-Image Enhancement,
pubmed-meshheading:14719691-Image Interpretation, Computer-Assisted,
pubmed-meshheading:14719691-Imaging, Three-Dimensional,
pubmed-meshheading:14719691-Magnetic Resonance Imaging,
pubmed-meshheading:14719691-Models, Biological,
pubmed-meshheading:14719691-Pattern Recognition, Automated,
pubmed-meshheading:14719691-Reproducibility of Results,
pubmed-meshheading:14719691-Sensitivity and Specificity,
pubmed-meshheading:14719691-Subtraction Technique
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pubmed:year |
2004
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pubmed:articleTitle |
Accurate template-based correction of brain MRI intensity distortion with application to dementia and aging.
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pubmed:affiliation |
Department of Radiology, University of California San Francisco, VAMC 114Q, Bldg. 9, Room 200 4150, Clement Street, San Francisco, CA 94121, USA. studholme@ieee.org
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pubmed:publicationType |
Journal Article,
Clinical Trial,
Comparative Study,
Research Support, U.S. Gov't, P.H.S.,
Controlled Clinical Trial,
Research Support, Non-U.S. Gov't,
Validation Studies
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