33 citations · 34 across the 5 of their papers we have counts for
5 papers · 1 filter
High-Resolution, Respiratory-Resolved Coronary MRA Using a Phyllotaxis-Reordered Variable-Density 3D Cones Trajectory
Srivathsan P. Koundinyan, Corey A. Baron, Mario O. Malave +6
Purpose: To develop a respiratory-resolved motion-compensation method for free-breathing, high-resolution coronary magnetic resonance angiography using a 3D cones trajectory. Metho…
Reconstruction of Undersampled 3D Non-Cartesian Image-Based Navigators for Coronary MRA Using an Unrolled Deep Learning Model
Mario O. Malavé, Corey A. Baron, Srivathsan P. Koundinyan +4
Purpose: To rapidly reconstruct undersampled 3D non-Cartesian image-based navigators (iNAVs) using an unrolled deep learning (DL) model for non-rigid motion correction in coronary…
Extreme MRI: Large-Scale Volumetric Dynamic Imaging from Continuous Non-Gated Acquisitions
Frank Ong, Xucheng Zhu, Joseph Y. Cheng +4
Purpose: To develop a framework to reconstruct large-scale volumetric dynamic MRI from rapid continuous and non-gated acquisitions, with applications to pulmonary and dynamic contr…
Computational MRI with Physics-based Constraints: Application to Multi-contrast and Quantitative Imaging
Jonathan I. Tamir, Frank Ong, Suma Anand +3
Compressed sensing takes advantage of low-dimensional signal structure to reduce sampling requirements far below the Nyquist rate. In magnetic resonance imaging (MRI), this often t…
Accelerating Non-Cartesian MRI Reconstruction Convergence using k-space Preconditioning
Frank Ong, Martin Uecker, Michael Lustig
We propose a k-space preconditioning formulation for accelerating the convergence of iterative Magnetic Resonance Imaging (MRI) reconstructions from non-uniformly sampled k-space d…