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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
2
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pubmed:dateCreated |
2007-2-5
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pubmed:abstractText |
In continuous wave (CW) electron paramagnetic resonance imaging (EPRI), high quality of reconstructed image along with fast and reliable data acquisition is highly desirable for many biological applications. An accurate representation of uniform distribution of projection data is necessary to ensure high reconstruction quality. The current techniques for data acquisition suffer from nonuniformities or local anisotropies in the distribution of projection data and present a poor approximation of a true uniform and isotropic distribution. In this work, we have implemented a technique based on Quasi-Monte Carlo method to acquire projections with more uniform and isotropic distribution of data over a 3D acquisition space. The proposed technique exhibits improvements in the reconstruction quality in terms of both mean-square-error and visual judgment. The effectiveness of the suggested technique is demonstrated using computer simulations and 3D EPRI experiments. The technique is robust and exhibits consistent performance for different object configurations and orientations.
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pubmed:grant |
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pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-10896858,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-11283999,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-12465117,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-12768597,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-15130284,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-15140431,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-15862233,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-15949747,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-16276490,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-16458030,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-1666622,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-3007920,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-7850182,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-8386044,
http://linkedlifedata.com/resource/pubmed/commentcorrection/17095271-8739367
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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 |
Feb
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pubmed:issn |
1090-7807
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pubmed:author |
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pubmed:issnType |
Print
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pubmed:volume |
184
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
236-45
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pubmed:dateRevised |
2011-8-1
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pubmed:meshHeading |
pubmed-meshheading:17095271-Algorithms,
pubmed-meshheading:17095271-Anisotropy,
pubmed-meshheading:17095271-Diagnostic Imaging,
pubmed-meshheading:17095271-Electron Spin Resonance Spectroscopy,
pubmed-meshheading:17095271-Image Enhancement,
pubmed-meshheading:17095271-Image Interpretation, Computer-Assisted,
pubmed-meshheading:17095271-Imaging, Three-Dimensional,
pubmed-meshheading:17095271-Monte Carlo Method,
pubmed-meshheading:17095271-Pattern Recognition, Automated,
pubmed-meshheading:17095271-Phantoms, Imaging,
pubmed-meshheading:17095271-Reproducibility of Results,
pubmed-meshheading:17095271-Sensitivity and Specificity
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pubmed:year |
2007
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pubmed:articleTitle |
Quasi Monte Carlo-based isotropic distribution of gradient directions for improved reconstruction quality of 3D EPR imaging.
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pubmed:affiliation |
Department of Electrical and Computer Engineering, The Ohio State University, College of Engineering, Columbus, OH 43210, USA.
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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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