APA
Click to copy
El-Rewaidy, H., Fahmy, A., Pashakhanloo, F., Cai, X., Kucukseymen, S., Csécs, I., … Nezafat, R. (2020). Multi‐domain convolutional neural network (MD‐CNN) for radial reconstruction of dynamic cardiac MRI. Magnetic Resonance in Medicine.
Chicago/Turabian
Click to copy
El-Rewaidy, Hossam, A. Fahmy, F. Pashakhanloo, Xiaoying Cai, S. Kucukseymen, I. Csécs, U. Neisius, Hassan Haji-Valizadeh, B. Menze, and R. Nezafat. “Multi‐Domain Convolutional Neural Network (MD‐CNN) for Radial Reconstruction of Dynamic Cardiac MRI.” Magnetic resonance in medicine (2020).
MLA
Click to copy
El-Rewaidy, Hossam, et al. “Multi‐Domain Convolutional Neural Network (MD‐CNN) for Radial Reconstruction of Dynamic Cardiac MRI.” Magnetic Resonance in Medicine, 2020.
BibTeX Click to copy
@article{hossam2020a,
title = {Multi‐domain convolutional neural network (MD‐CNN) for radial reconstruction of dynamic cardiac MRI},
year = {2020},
journal = {Magnetic resonance in medicine},
author = {El-Rewaidy, Hossam and Fahmy, A. and Pashakhanloo, F. and Cai, Xiaoying and Kucukseymen, S. and Csécs, I. and Neisius, U. and Haji-Valizadeh, Hassan and Menze, B. and Nezafat, R.}
}
Cardiac MR cine imaging allows accurate and reproducible assessment of cardiac function. However, its long scan time not only limits the spatial and temporal resolutions but is challenging in patients with breath‐holding difficulty or non‐sinus rhythms. To reduce scan time, we propose a multi‐domain convolutional neural network (MD‐CNN) for fast reconstruction of highly undersampled radial cine images.
