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Dual-contrast and dual-phase first-pass myocardial perfusion using simultaneous multi-slice imaging

The effect of a dynamic inversion time in high-resolution isotropic 3D dark-blood LGE without additional magnetization preparation

Extra-cellular volume (ECV) mapping using fast single-breathhold 2D multi-slice myocardial T1 mapping (FAST1) at 1.5T

Fast single-breathhold 2D multi-slice myocardial T1 mapping (FAST1) at 3T for time-efficient full left ventricular coverage

Fully automated assessment of myocardial ischemic burden – a joint perfusion and viability mapping approach

Fully automated detection of the quiescent phases of the cardiac cycle from CINE images using deep learning

Author:Naledi Adam  James Clough  Ronald Mooiweer  Phuoc Dong  Li Huang  Reza Razavi  Kuberan Pushparajah  Amedeo Chiribiri  Andrew King  Sébastien Roujol  

Institution:King's College London  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:Cardiovascular Applications  

Session Name:Cardiac Function 2  

Program Number:2175  

Room Live Q&A Session:

Fully automated quantification of left ventricular scar in patients with ischemic heart disease using deep learning and Gaussian mixture models

­­­­Improved precision of T1 estimation for 1.5T quantitative myocardial perfusion imaging using a high flip angle SSFP reference image

Author:Sarah McElroy  Sohaib Nazir  Karl Kunze  Radhouene Neji  Amedeo Chiribiri  Sébastien Roujol  

Institution:King's College London  Siemens Healthcare Limited  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:Myocardial Tissue Characterization and Perfusion  

Session Name:CMR Perfusion Imaging  

Program Number:2094  

Room Live Q&A Session:

Model-based quantitative mapping for highly accelerated ?rst-pass perfusion cardiac MRI

Myocardial perfusion quantification by cardiovascular magnetic resonance is significantly affected by the arterial input sampling location

SMS-bSSFP perfusion imaging with high spatial resolution and coverage using pseudorandom undersampling and compressed sensing reconstruction