A stepwise strategy integrating dynamic stress CT myocardial perfusion and deep learning-based FFRCT in the work-up of stable coronary artery disease
10.1007/s00330-023-10562-x · doi-reference
Deep learning-based quantitative CT myocardial perfusion imaging and risk stratification of coronary artery disease
10.1148/radiol.242570 · doi-reference
Automated identification of myocardial perfusion defects in dynamic cardiac computed tomography using deep learning
10.1016/j.ejmp.2023.102555 · doi-reference
DnCNN-based denoising model for low-dose myocardial CT perfusion imaging
10.3390/electronics15010124 · doi-reference
Deep learning-based image registration in dynamic myocardial perfusion CT imaging
10.1109/tmi.2022.3214380 · doi-reference
Differentiating macrovascular and microvascular ischemia using fractal analysis of dynamic myocardial perfusion stress-CT
10.1097/rli.0000000000001027 · doi-reference
Radiomics analysis enhances the diagnostic performance of CMR stress perfusion: a proof-of-concept study using the Dan-NICAD dataset
10.3389/fcvm.2023.1141026 · doi-reference
Development of a deep learning algorithm for detecting significant coronary artery stenosis in whole-heart coronary magnetic resonance angiography
10.1016/j.jocmr.2025.101932 · doi-reference
AI cardiac MRI scar analysis aids prediction of major arrhythmic events in the multicenter DERIVATE registry
10.1148/radiol.222239 · doi-reference
A survey on deep learning in medical image analysis
10.1016/j.media.2017.07.005 · doi-reference
Automated inline analysis of myocardial perfusion MRI with deep learning
10.1148/ryai.2020200009 · doi-reference
Simultaneous (13)N-Ammonia and gadolinium first-pass myocardial perfusion with quantitative hybrid PET-MR imaging: a phantom and clinical feasibility study
10.1186/s41824-019-0062-6 · doi-reference
Underestimation of myocardial blood flow by dynamic perfusion CT: explanations by two-compartment model analysis and limited temporal sampling of dynamic CT
10.1016/j.jcct.2016.01.008 · doi-reference
Artefact-free late gadolinium enhancement imaging in patients with implanted cardiac devices using a modified broadband sequence: current strategies and results from a real-world patient cohort
10.1093/europace/eux016 · doi-reference
Emerging applications for ferumoxytol as a contrast agent in MRI: emerging applications of ferumoxytol
10.1002/jmri.24691 · doi-reference
Feasibility of computed tomography perfusion for detection of cardiac allograft rejection following heart transplantation
10.1016/j.jcmg.2020.01.004 · doi-reference
CT coronary angiography and dynamic CT myocardial perfusion for detection of cardiac allograft vasculopathy
10.1016/j.jcmg.2022.12.031 · doi-reference
Test-retest reproducibility of absolute myocardial blood flow obtained using stress dynamic CT myocardial perfusion imaging
10.1016/j.ijcha.2024.101510 · doi-reference
Integrating myocardial CT perfusion with coronary CT angiography improves risk stratification in patients with dialysis-dependent end-stage renal disease
10.1007/s11604-024-01690-5 · doi-reference
Longer diabetes duration reduces myocardial blood flow in remote myocardium assessed by dynamic myocardial CT perfusion
10.1016/j.jdiacomp.2018.03.003 · doi-reference
Prognostic value of stress dynamic computed tomography perfusion with computed tomography delayed enhancement
10.1016/j.jcmg.2019.12.017 · doi-reference
Incremental prognostic value of myocardial blood flow quantified with stress dynamic computed tomography perfusion imaging
10.1016/j.jcmg.2018.05.021 · doi-reference
Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease
10.1016/j.jcct.2019.02.005 · doi-reference
Prognostic significance of stress dynamic myocardial CT perfusion: comparison with CT-FFR and CT angiography stenosis-the multicenter VALIDITY trial
10.1007/s00330-024-11187-4 · doi-reference
Global quantification of left ventricular myocardial perfusion at dynamic CT imaging: prognostic value
10.1016/j.jcct.2016.12.003 · doi-reference
Clinical validation of the accuracy of absolute myocardial blood flow quantification with dual-source CT using 15O-water PET
10.1148/ryct.2021210060 · doi-reference
Relationship between microvascular status and diagnostic performance of stress dynamic CT perfusion imaging
10.1007/s00330-024-11136-1 · doi-reference
Diagnostic accuracy of dynamic stress myocardial CT perfusion compared with invasive physiology in patients with stents: the advantage 2 study
10.1148/radiol.232225 · doi-reference
Knowledge of hyperemic myocardial blood flow in healthy subjects helps identify myocardial ischemia in patients with coronary artery disease
10.3389/fcvm.2022.817911 · doi-reference
Dynamic myocardial perfusion CT for the detection of hemodynamically significant coronary artery disease
10.1016/j.jcmg.2021.07.021 · doi-reference
Diagnostic performance of quantitative, semi-quantitative, and visual analysis of dynamic CT myocardial perfusion imaging: a validation study with invasive fractional flow reserve
10.1007/s00330-020-07145-5 · doi-reference
Diagnostic performance of dynamic myocardial perfusion imaging using dual-source computed tomography
10.1016/j.jacc.2021.08.067 · doi-reference
Stress myocardial blood flow ratio by dynamic CT perfusion identifies hemodynamically significant CAD
10.1016/j.jcmg.2019.06.016 · doi-reference
Incremental diagnostic value of whole-heart dynamic computed tomography perfusion imaging for detecting obstructive coronary artery disease
10.1016/j.jjcc.2018.12.006 · doi-reference
Dynamic stress computed tomography perfusion with a whole-heart coverage scanner in addition to coronary computed tomography angiography and fractional flow reserve computed tomography derived
10.1016/j.jcmg.2019.02.015 · doi-reference
Detection of hemodynamically significant coronary stenosis: CT myocardial perfusion versus machine learning CT fractional flow reserve
10.1148/radiol.2019190098 · doi-reference
Integrating CT myocardial perfusion and CT-FFR in the work-up of coronary artery disease
10.1016/j.jcmg.2016.09.028 · doi-reference
Diagnostic accuracy of endocardial-to-epicardial myocardial blood flow ratio for the detection of significant coronary artery disease with dynamic myocardial perfusion dual-source computed tomography
10.1253/circj.cj-16-1319 · doi-reference
Dynamic computed tomography myocardial perfusion imaging: comparison of clinical analysis methods for the detection of vessel-specific ischemia
10.1161/circimaging.116.005505 · doi-reference
Relative myocardial blood flow by dynamic computed tomographic perfusion imaging predicts hemodynamic significance of coronary stenosis better than absolute blood flow
10.1097/rli.0000000000000087 · doi-reference
