The impact of iterative reconstruction algorithms on machine learning-based coronary CT angiography-derived fractional flow reserve (CT-FFRML) values

To evaluate the impact of an iterative reconstruction (IR) algorithm (advanced modeled iterative reconstruction, ADMIRE) on machine learning-based coronary computed tomography angiography–derived fractional flow reserve (CT-FFR ML ) measurements compared with filtered back projection (FBP). 170 plaq...

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Veröffentlicht in:	The International Journal of Cardiovascular Imaging Jg. 36; H. 6; S. 1177 - 1185
Hauptverfasser:	Li, Shujiao, Chen, Chihua, Qin, Le, Gu, Shengjia, Zhang, Huan, Yan, Fuhua, Yang, Wenjie
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.06.2020 Springer Nature B.V
Schlagworte:	Algorithms Angiography Blood vessels Cardiac Imaging Cardiology Computed tomography Datasets Image reconstruction Imaging Ischemia Iterative methods Learning algorithms Machine learning Medical imaging Medicine Medicine & Public Health Original Paper Plaques Radiology Stenosis Subgroups Myocardial fractional flow reserve Coronary computed tomography angiography Image reconstruction Machine learning Coronary stenosis
ISSN:	1569-5794, 1875-8312, 1573-0743, 1875-8312
Online-Zugang:	Volltext
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