29 citations · 35 across the 9 of their papers we have counts for
10 papers
Prospectively accelerated dynamic speech MRI at 3 Tesla using a self-navigated spiral based manifold regularized scheme
Rushdi Zahid Rusho, Abdul Haseeb Ahmed, Stanley Kruger +6
This work proposes a self-navigated variable density spiral(VDS) based manifold regularization scheme to prospectively improve dynamic speech MRI at 3T. Short readout 1.3ms spirals…
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…
Dynamic Imaging using Deep Bi-linear Unsupervised Regularization (DEBLUR)
Abdul Haseeb Ahmed, Prashant Nagpal, Mathews Jacob
Bilinear models that decompose dynamic data to spatial and temporal factors are powerful and memory-efficient tools for the recovery of dynamic MRI data. These methods rely on spar…
Dynamic imaging using a deep generative SToRM (Gen-SToRM) model
Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal +2
We introduce a generative smoothness regularization on manifolds (SToRM) model for the recovery of dynamic image data from highly undersampled measurements. The model assumes that…
Deep Generative SToRM model for dynamic imaging
Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal +2
We introduce a novel generative smoothness regularization on manifolds (SToRM) model for the recovery of dynamic image data from highly undersampled measurements. The proposed gene…
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…
Dynamic MRI using deep manifold self-learning
Abdul Haseeb Ahmed, Hemant Aggarwal, Prashant Nagpal +1
We propose a deep self-learning algorithm to learn the manifold structure of free-breathing and ungated cardiac data and to recover the cardiac CINE MRI from highly undersampled me…
Motion correction in cardiac perfusion data by using robust matrix decomposition
Abdul Haseeb Ahmed, Ijaz M. Qureshi
Motion free reconstruction of compressively sampled cardiac perfusion MR images is a challenging problem. It is due to the aliasing artifacts and the rapid contrast changes in the…
Efficient Reconstruction of Free Breathing Under-Sampled Cardiac Cine MRI
Abdul Haseeb Ahmed, Ijaz M. Qureshi, Jawad Ali Shah +1
Respiratory motion can cause strong blurring artifacts in the reconstructed image during MR acquisition. These artifacts become more prominent when use in the presence of undersamp…
Free-breathing and ungated cardiac cine using navigator-less spiral SToRM
Abdul Haseeb Ahmed, Ruixi Zhou, Yang Yang +3
We introduce a kernel low-rank algorithm to recover free-breathing and ungated dynamic MRI from spiral acquisitions without explicit k-space navigators. It is often challenging for…