70 citations · 70 across the 4 of their papers we have counts for
6 papers
BMART-Enabled Field-Map Combination of Projection-Reconstruction Phase-Cycled SSFP Cardiac Cine for Banding and Flow-Artifact Reduction
Anjali Datta, Dwight G Nishimura, Corey A Baron
Purpose: To develop a method for banding-free bSSFP cardiac cine with substantially reduced flow artifacts. Methods: A projection-reconstruction (PR) trajectory is proposed for a f…
Anisotropic field-of-views in radial imaging
Peder E. Z. Larson, Paul T. Gurney, Dwight G. Nishimura
Radial imaging techniques, such as projection-reconstruction (PR), are used in magnetic resonance imaging (MRI) for dynamic imaging, angiography, and short-imaging. They are robust…
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…
Unraveling the Effect of Spatial Resolution and Scan Acceleration on 3D Image-Based Navigators for Respiratory Motion Tracking in Coronary MR Angiography
Srivathsan P. Koundinyan, Joseph Y. Cheng, Mario O. Malave +4
Purpose: To study the accuracy of motion information extracted from beat-to-beat 3D image-based navigators (3D iNAVs) collected using a variable-density cones trajectory with diffe…
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…
Deep Residual Network for Off-Resonance Artifact Correction with Application to Pediatric Body Magnetic Resonance Angiography with 3D Cones
David Y Zeng, Jamil Shaikh, Dwight G Nishimura +2
Purpose: Off-resonance artifact correction by deep-learning, to facilitate rapid pediatric body imaging with a scan time efficient 3D cones trajectory. Methods: A residual convolut…