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.
MeSH Number(s)
E01.158.600.680
E01.370.350.350.700
E01.370.350.700.705
L01.700.508.100.158.600.680
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 Harvard Catalyst Profiles by year, and whether "Radiographic Image Interpretation, Computer-Assisted" was a major or minor topic of these publication.
To see the data from this visualization as text,
click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 1993 | 1 | 0 | 1 |
| 1995 | 1 | 0 | 1 |
| 1997 | 1 | 0 | 1 |
| 1998 | 1 | 0 | 1 |
| 1999 | 1 | 0 | 1 |
| 2000 | 3 | 2 | 5 |
| 2001 | 1 | 0 | 1 |
| 2002 | 4 | 0 | 4 |
| 2003 | 7 | 1 | 8 |
| 2004 | 19 | 4 | 23 |
| 2005 | 14 | 4 | 18 |
| 2006 | 14 | 5 | 19 |
| 2007 | 28 | 11 | 39 |
| 2008 | 18 | 19 | 37 |
| 2009 | 24 | 13 | 37 |
| 2010 | 21 | 22 | 43 |
| 2011 | 19 | 13 | 32 |
| 2012 | 26 | 21 | 47 |
| 2013 | 33 | 29 | 62 |
| 2014 | 31 | 22 | 53 |
| 2015 | 20 | 24 | 44 |
| 2016 | 15 | 11 | 26 |
| 2017 | 16 | 22 | 38 |
| 2018 | 24 | 10 | 34 |
| 2019 | 11 | 18 | 29 |
| 2020 | 14 | 13 | 27 |
| 2021 | 6 | 15 | 21 |
| 2022 | 0 | 5 | 5 |
| 2023 | 0 | 1 | 1 |
Below are the most recent publications written about "Radiographic Image Interpretation, Computer-Assisted" by people in Profiles.
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A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis. JAMA Netw Open. 2023 02 01; 6(2):e230524.
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Computer-aided Detection of Polyps Does Not Improve Colonoscopist Performance in a Pragmatic Implementation Trial. Gastroenterology. 2023 03; 164(3):481-483.e6.
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CT image quality evaluation in the age of deep learning: trade-off between functionality and fidelity. Eur Radiol. 2023 Apr; 33(4):2439-2449.
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Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely? Eur Radiol. 2023 Mar; 33(3):1629-1640.
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Detection of Incidental Nonosseous Thoracic Pathology on State-of-the-Art Ultralow-Dose Protocol Computed Tomography in Pediatric Patients With Pectus Excavatum. J Comput Assist Tomogr. 2022 May-Jun 01; 46(3):492-498.
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Virtual Unenhanced Images: Qualitative and Quantitative Comparison Between Different Dual-Energy CT Scanners in a Patient and Phantom Study. Invest Radiol. 2022 01 01; 57(1):52-61.
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Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence. Radiology. 2022 03; 302(3):627-636.
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Visible Human Project® female surface based computational phantom (Nelly) for radio-frequency safety evaluation in MRI coils. PLoS One. 2021; 16(12):e0260922.
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An Artificial Intelligence-Based Chest X-ray Model on Human Nodule Detection Accuracy From a Multicenter Study. JAMA Netw Open. 2021 12 01; 4(12):e2141096.
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Assessing the utility of low resolution brain imaging: treatment of infant hydrocephalus. Neuroimage Clin. 2021; 32:102896.