Automated estimation of image quality for coronary computed tomographic angiography using machine learning
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Title
Automated estimation of image quality for coronary computed tomographic angiography using machine learning
Authors
Keywords
Computed tomography angiography, Coronary vessels, Cardiac imaging techniques, Machine learning, Image enhancement
Journal
EUROPEAN RADIOLOGY
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2018-03-23
DOI
10.1007/s00330-018-5348-8
References
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Related references
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- Evaluation of high-pitch dual-source CT angiography for evaluation of coronary and carotid-cerebrovascular arteries
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- SCCT guidelines for the interpretation and reporting of coronary CT angiography: A report of the Society of Cardiovascular Computed Tomography Guidelines Committee
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- Diagnostic Accuracy of Fractional Flow Reserve From Anatomic CT Angiography
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- (2012) James K. Min et al. Journal of Cardiovascular Computed Tomography
- Diagnosis of Ischemia-Causing Coronary Stenoses by Noninvasive Fractional Flow Reserve Computed From Coronary Computed Tomographic Angiograms
- (2011) Bon-Kwon Koo et al. JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
- Rationale and design of the DeFACTO (Determination of Fractional Flow Reserve by Anatomic Computed Tomographic AngiOgraphy) study
- (2011) James K. Min et al. Journal of Cardiovascular Computed Tomography
- Adaptive Statistical Iterative Reconstruction: Assessment of Image Noise and Image Quality in Coronary CT Angiography
- (2010) Jonathon Leipsic et al. AMERICAN JOURNAL OF ROENTGENOLOGY
- Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification
- (2008) H. Fronthaler et al. IEEE Transactions on Information Forensics and Security
- Diagnostic Performance of 64-Multidetector Row Coronary Computed Tomographic Angiography for Evaluation of Coronary Artery Stenosis in Individuals Without Known Coronary Artery Disease
- (2008) Matthew J. Budoff et al. JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
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