37 citations · 151 across the 11 of their papers we have counts for
11 papers
Model-Based Reconstruction for Joint Estimation of , and Field Maps Using Single-Shot Inversion-Recovery Multi-Echo Radial FLASH
Xiaoqing Wang, Nick Scholand, Zhengguo Tan +5
Purpose: To develop a model-based nonlinear reconstruction for simultaneous water-specific , , field and/or fat fraction (FF) mapping using single-shot in…
Improved Multi-Shot Diffusion-Weighted MRI with Zero-Shot Self-Supervised Learning Reconstruction
Jaejin Cho, Yohan Jun, Xiaoqing Wang +2
Diffusion MRI is commonly performed using echo-planar imaging (EPI) due to its rapid acquisition time. However, the resolution of diffusion-weighted images is often limited by magn…
Generative Priors for MRI Reconstruction Trained from Magnitude-Only Images Using Phase Augmentation
Guanxiong Luo, Xiaoqing Wang, Mortiz Blumenthal +5
Purpose: In this work, we present a workflow to construct generic and robust generative image priors from magnitude-only images. The priors can then be used for regularization in r…
Zero-DeepSub: Zero-Shot Deep Subspace Reconstruction for Rapid Multiparametric Quantitative MRI Using 3D-QALAS
Yohan Jun, Yamin Arefeen, Jaejin Cho +7
Purpose: To develop and evaluate methods for 1) reconstructing 3D-quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) time-ser…
SSL-QALAS: Self-Supervised Learning for Rapid Multiparameter Estimation in Quantitative MRI Using 3D-QALAS
Yohan Jun, Jaejin Cho, Xiaoqing Wang +4
Purpose: To develop and evaluate a method for rapid estimation of multiparametric T1, T2, proton density (PD), and inversion efficiency (IE) maps from 3D-quantification using an in…
Quantitative Magnetic Resonance Imaging by Nonlinear Inversion of the Bloch Equations
Nick Scholand, Xiaoqing Wang, Volkert Roeloffs +2
Purpose: Development of a generic model-based reconstruction framework for multi-parametric quantitative MRI that can be used with data from different pulse sequences. Methods: Gen…
WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstruction
Zongjiang Tu, Die Liu, Xiaoqing Wang +6
Deep learning based parallel imaging (PI) has made great progresses in recent years to accelerate magnetic resonance imaging (MRI). Nevertheless, it still has some limitations, suc…
Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction
Xiaoqing Wang, Sebastian Rosenzweig, Volkert Roeloffs +7
Purpose: To develop a free-breathing myocardial T1 mapping technique using inversion-recovery (IR) radial fast low-angle shot (FLASH) and calibrationless motion-resolved model-base…
Free-Breathing Liver Fat, and Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction
Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal +6
This work introduced a stack-of-radial multi-echo asymmetric-echo MRI sequence for free-breathing liver volumetric acquisition. Regularized model-based reconstruction was implement…
Physics-based Reconstruction Methods for Magnetic Resonance Imaging
Xiaoqing Wang, Zhengguo Tan, Nick Scholand +2
Conventional Magnetic Resonance Imaging (MRI) is hampered by long scan times and only qualitative image contrasts that prohibit a direct comparison between different systems. To ad…
Model-Based Reconstruction for Simultaneous Multi-Slice T1 Mapping using Single-Shot Inversion-Recovery Radial FLASH
Xiaoqing Wang, Sebastian Rosenzweig, Nick Scholand +2
Purpose: To develop a single-shot multi-slice T1 mapping method by combing simultaneous multi-slice (SMS) excitations, single-shot inversion-recovery (IR) radial fast low-angle sho…