 Signal-To-Noise Ratio
"Signal-To-Noise Ratio" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
The comparison of the quantity of meaningful data to the irrelevant or incorrect data.
| Descriptor ID |
D059629
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| MeSH Number(s) |
E05.318.740.872.875 E05.318.780.800.875 G17.800.500 N05.715.360.750.725.750 N05.715.360.780.700.840 N06.850.520.445.800.875 N06.850.520.830.872.750
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| Concept/Terms |
Signal-To-Noise Ratio- Signal-To-Noise Ratio
- Ratio, Signal-To-Noise
- Ratios, Signal-To-Noise
- Signal To Noise Ratio
- Signal-To-Noise Ratios
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Below are MeSH descriptors whose meaning is more general than "Signal-To-Noise Ratio".
Below are MeSH descriptors whose meaning is more specific than "Signal-To-Noise Ratio".
This graph shows the total number of publications written about "Signal-To-Noise Ratio" by people in this website by year, and whether "Signal-To-Noise Ratio" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 2012 | 0 | 2 | 2 | | 2013 | 1 | 2 | 3 | | 2014 | 0 | 13 | 13 | | 2015 | 0 | 5 | 5 | | 2016 | 0 | 2 | 2 | | 2017 | 0 | 9 | 9 | | 2018 | 1 | 7 | 8 | | 2019 | 0 | 3 | 3 | | 2020 | 0 | 1 | 1 | | 2021 | 1 | 0 | 1 |
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Below are the most recent publications written about "Signal-To-Noise Ratio" by people in Profiles.
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Fan X, Chatterjee A, Medved M, Oto A, Karczmar GS. Signal intensity form of the Tofts model for quantitative analysis of prostate dynamic contrast enhanced MRI data. Phys Med Biol. 2021 01 22; 66(2):025002.
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Sugino M, Shiraishi J. [Application of Convolutional Neural Network for Evaluating CT Dose Using Image Noise Classification: A Phantom Study]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2020; 76(11):1143-1151.
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Bastiaansen JAM, Piccini D, Di Sopra L, Roy CW, Heerfordt J, Edelman RR, Koktzoglou I, Yerly J, Stuber M. Natively fat-suppressed 5D whole-heart MRI with a radial free-running fast-interrupted steady-state (FISS) sequence at 1.5T and 3T. Magn Reson Med. 2020 01; 83(1):45-55.
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Pineda F, Sheth D, Abe H, Medved M, Karczmar GS. Low-dose imaging technique (LITE) MRI: initial experience in breast imaging. Br J Radiol. 2019 Nov; 92(1103):20190302.
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Rajiah P, Ciancibello L, Novak R, Sposato J, Landeras L, Gilkeson R. Ultra-low dose contrast CT pulmonary angiography in oncology patients using a high-pitch helical dual-source technology. Diagn Interv Radiol. 2019 May; 25(3):195-203.
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Sahiner B, Pezeshk A, Hadjiiski LM, Wang X, Drukker K, Cha KH, Summers RM, Giger ML. Deep learning in medical imaging and radiation therapy. Med Phys. 2019 Jan; 46(1):e1-e36.
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Fukui R, Shiraishi J. Application of a pixel-shifted linear interpolation technique for reducing the projection number in tomosynthesis imaging. Radiol Phys Technol. 2019 Mar; 12(1):30-39.
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Newitt DC, Zhang Z, Gibbs JE, Partridge SC, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Aliu S, Li W, Cimino L, Joe BN, Umphrey H, Ojeda-Fournier H, Dogan B, Oh K, Abe H, Drukteinis J, Esserman LJ, Hylton NM. Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial. J Magn Reson Imaging. 2019 06; 49(6):1617-1628.
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Deh K, Kawaji K, Bulk M, Van Der Weerd L, Lind E, Spincemaille P, McCabe Gillen K, Van Auderkerke J, Wang Y, Nguyen TD. Multicenter reproducibility of quantitative susceptibility mapping in a gadolinium phantom using MEDI+0 automatic zero referencing. Magn Reson Med. 2019 02; 81(2):1229-1236.
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Chen B, Zhang Z, Xia D, Sidky EY, Pan X. Algorithm-enabled partial-angular-scan configurations for dual-energy CT. Med Phys. 2018 May; 45(5):1857-1870.
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