Source:http://linkedlifedata.com/resource/pubmed/id/20175486
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Predicate | Object |
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rdf:type | |
lifeskim:mentions | |
pubmed:issue |
1
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pubmed:dateCreated |
2010-2-23
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pubmed:abstractText |
To optimize radiation dose efficiency in CT while maintaining image quality, it is important to select the optimal tube potential. The selection of optimal tube potential, however, is highly dependent on patient size and diagnostic task. The purpose of this work was to develop a general strategy that allows for automatic tube potential selection for each individual patient and each diagnostic task.
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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 |
Jan
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pubmed:issn |
0094-2405
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pubmed:author | |
pubmed:issnType |
Print
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pubmed:volume |
37
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
234-43
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pubmed:meshHeading |
pubmed-meshheading:20175486-Algorithms,
pubmed-meshheading:20175486-Body Burden,
pubmed-meshheading:20175486-Humans,
pubmed-meshheading:20175486-Radiation Dosage,
pubmed-meshheading:20175486-Radiation Protection,
pubmed-meshheading:20175486-Radiometry,
pubmed-meshheading:20175486-Reproducibility of Results,
pubmed-meshheading:20175486-Sensitivity and Specificity,
pubmed-meshheading:20175486-Tomography, X-Ray Computed
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pubmed:year |
2010
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pubmed:articleTitle |
Automatic selection of tube potential for radiation dose reduction in CT: a general strategy.
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pubmed:affiliation |
Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905, USA. yu.lifeng@mayo.edu
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pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
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