 Radiographic Image Interpretation, Computer-Assisted
"Radiographic Image Interpretation, Computer-Assisted" 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.
Computer systems or networks designed to provide radiographic interpretive information.
| Descriptor ID |
D011857
|
| MeSH Number(s) |
E01.158.600.680 E01.370.350.350.700 E01.370.350.700.705 L01.700.508.100.158.600.680
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| Concept/Terms |
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Below are MeSH descriptors whose meaning is more general than "Radiographic Image Interpretation, Computer-Assisted".
- Analytical, Diagnostic and Therapeutic Techniques and Equipment [E]
- Diagnosis [E01]
- Diagnosis, Computer-Assisted [E01.158]
- Image Interpretation, Computer-Assisted [E01.158.600]
- Radiographic Image Interpretation, Computer-Assisted [E01.158.600.680]
- Diagnostic Techniques and Procedures [E01.370]
- Diagnostic Imaging [E01.370.350]
- Image Interpretation, Computer-Assisted [E01.370.350.350]
- Radiographic Image Interpretation, Computer-Assisted [E01.370.350.350.700]
- Radiography [E01.370.350.700]
- Radiographic Image Interpretation, Computer-Assisted [E01.370.350.700.705]
- Information Science [L]
- Information Science [L01]
- Medical Informatics [L01.700]
- Medical Informatics Applications [L01.700.508]
- Decision Making, Computer-Assisted [L01.700.508.100]
- Diagnosis, Computer-Assisted [L01.700.508.100.158]
- Image Interpretation, Computer-Assisted [L01.700.508.100.158.600]
- Radiographic Image Interpretation, Computer-Assisted [L01.700.508.100.158.600.680]
Below are MeSH descriptors whose meaning is more specific than "Radiographic Image Interpretation, Computer-Assisted".
This graph shows the total number of publications written about "Radiographic Image Interpretation, Computer-Assisted" by people in this website by year, and whether "Radiographic Image Interpretation, Computer-Assisted" 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 |
|---|
| 1987 | 1 | 1 | 2 | | 1988 | 4 | 0 | 4 | | 1990 | 4 | 1 | 5 | | 1991 | 1 | 0 | 1 | | 1992 | 4 | 0 | 4 | | 1993 | 9 | 1 | 10 | | 1994 | 4 | 1 | 5 | | 1995 | 4 | 1 | 5 | | 1996 | 4 | 2 | 6 | | 1997 | 1 | 3 | 4 | | 1998 | 6 | 0 | 6 | | 1999 | 0 | 1 | 1 | | 2000 | 1 | 3 | 4 | | 2001 | 1 | 2 | 3 | | 2002 | 9 | 0 | 9 | | 2003 | 9 | 1 | 10 | | 2004 | 21 | 3 | 24 | | 2005 | 20 | 4 | 24 | | 2006 | 18 | 7 | 25 | | 2007 | 13 | 2 | 15 | | 2008 | 11 | 2 | 13 | | 2009 | 9 | 7 | 16 | | 2010 | 7 | 1 | 8 | | 2011 | 5 | 8 | 13 | | 2012 | 6 | 2 | 8 | | 2013 | 7 | 3 | 10 | | 2014 | 5 | 4 | 9 | | 2015 | 5 | 3 | 8 | | 2016 | 3 | 0 | 3 | | 2017 | 1 | 4 | 5 | | 2018 | 2 | 1 | 3 | | 2019 | 3 | 1 | 4 | | 2020 | 0 | 3 | 3 |
To return to the timeline, click here.
Below are the most recent publications written about "Radiographic Image Interpretation, Computer-Assisted" by people in Profiles.
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Wang CY, Foy JJ, Siewert TY, Haraf DJ, Ginat DT. Baseline Computed Tomography Radiomic and Genomic Assessment of Head and Neck Squamous Cell Carcinoma. J Comput Assist Tomogr. 2020 Jul/Aug; 44(4):546-552.
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Alavanja A, Parker K, Ginat DT. Magnetic Resonance Imaging Findings of Crystalloid-Containing Parotid Cysts. J Comput Assist Tomogr. 2020 Jul/Aug; 44(4):569-570.
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Schonberger M, Lefere P, Dachman AH. Pearls and Pitfalls of Interpretation in CT Colonography. Can Assoc Radiol J. 2020 May; 71(2):140-148.
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Mozaffary A, Trabzonlu TA, Lombardi P, Seyal AR, Agrawal R, Yaghmai V. Integration of fully automated computer-aided pulmonary nodule detection into CT pulmonary angiography studies in the emergency department: effect on workflow and diagnostic accuracy. Emerg Radiol. 2019 Dec; 26(6):609-614.
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Patel AR, Maffessanti F, Patel MB, Kebed K, Narang A, Singh A, Medvedofsky D, Zaidi SJ, Mediratta A, Goyal N, Kachenoura N, Lang RM, Mor-Avi V. Hemodynamic impact of coronary stenosis using computed tomography: comparison between noninvasive fractional flow reserve and 3D fusion of coronary angiography with stress myocardial perfusion. Int J Cardiovasc Imaging. 2019 Sep; 35(9):1733-1743.
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Robinson K, Li H, Lan L, Schacht D, Giger M. Radiomics robustness assessment and classification evaluation: A two-stage method demonstrated on multivendor FFDM. Med Phys. 2019 May; 46(5):2145-2156.
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Balaney B, Vembar M, Grass M, Singh A, Kawaji K, Landeras L, Chung J, Mor-Avi V, Patel AR. Improved visualization of the coronary arteries using motion correction during vasodilator stress CT myocardial perfusion imaging. Eur J Radiol. 2019 May; 114:1-5.
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Drukker K, Giger ML, Joe BN, Kerlikowske K, Greenwood H, Drukteinis JS, Niell B, Fan B, Malkov S, Avila J, Kazemi L, Shepherd J. Combined Benefit of Quantitative Three-Compartment Breast Image Analysis and Mammography Radiomics in the Classification of Breast Masses in a Clinical Data Set. Radiology. 2019 03; 290(3):621-628.
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Mendel K, Li H, Sheth D, Giger M. Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography. Acad Radiol. 2019 06; 26(6):735-743.
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Jones KC, Redler G, Templeton A, Bernard D, Turian JV, Chu JCH. Characterization of Compton-scatter imaging with an analytical simulation method. Phys Med Biol. 2018 01 11; 63(2):025016.
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