3 papers
eess.IV2023
Motion Compensated Unsupervised Deep Learning for 5D MRI
Joseph Kettelkamp, Ludovica Romanin, Davide Piccini +2
We propose an unsupervised deep learning algorithm for the motion-compensated reconstruction of 5D cardiac MRI data from 3D radial acquisitions. Ungated free-breathing 5D MRI simpl…
eess.IV2021
Joint alignment and reconstruction of multislice dynamic MRI using variational manifold learning
Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal +3
Free-breathing cardiac MRI schemes are emerging as competitive alternatives to breath-held cine MRI protocols, enabling applicability to pediatric and other population groups that…
eess.IV2021
Variational manifold learning from incomplete data: application to multislice dynamic MRI
Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal +3
Current deep learning-based manifold learning algorithms such as the variational autoencoder (VAE) require fully sampled data to learn the probability density of real-world dataset…