128 citations · 486 across the 38 of their papers we have counts for
43 papers
High-Temporal-Resolution Motion Correction in Magnetic Resonance Fingerprinting Using a Quantitative Scout and Compact Spiral Navigators
Aizada Nurdinova, Xiaozhi Cao, Daniel R. Abraham +6
Motion correction in magnetic resonance fingerprinting (MRF) helps preserve the accuracy of quantitative maps; however, existing approaches provide motion updates only every 7-8 se…
Distortion-Corrected Diffusion MRI Using Rotated-View EPI and Joint Field-Map/Image Estimation with Gaussian Primitives
Wenqi Huang, Zhitao Li, Nan Wang +8
Echo Planar Imaging (EPI) is the standard acquisition technique for diffusion and functional neuroimaging, enabling rapid imaging but suffering from geometric distortions caused by…
Fast Voxelwise SNR Estimation for Iterative MRI Reconstructions
Onat Dalmaz, Daniel Abraham, Alexander R. Toews +3
Purpose: To develop a fast, general-purpose framework for voxelwise noise characterization in linear and nonlinear iterative MRI reconstructions, recovering the image-domain noise…
Fully 3D Unrolled Magnetic Resonance Fingerprinting Reconstruction via Staged Pretraining and Implicit Gridding
Yonatan Urman, Mark Nishimura, Daniel Abraham +2
Magnetic Resonance Fingerprinting (MRF) enables fast quantitative imaging, yet reconstructing high-resolution 3D data remains computationally demanding. Non-Cartesian reconstructio…
A dynamic shim approach for correcting eddy current effects in diffusion-prepared MRI acquisition using a multi-coil AC/DC shim-array
Congyu Liao, Jason P. Stockmann, Zhitao Li +18
Purpose: We developed a dynamic B0 shimming approach using a 46-channel AC/DC shim array to correct phase errors caused by eddy currents from diffusion-encoding gradients in diffus…
Fast Reconstruction of Motion-Corrupted Data with Mobile-GRAPPA: Motion and dB0 Inhomogeneity Correction Leveraging Efficient GRAPPA
Yimeng Lin, Nan Wang, Daniel Abraham +5
Advanced motion navigations now enable rapid tracking of subject motion and dB0-induced phase, but accurately incorporating this high-temporal-resolution information into SENSE (Al…
Enhancing Diffusion-Weighted Images (DWI) for Diffusion MRI: Is it Enough without Non-Diffusion-Weighted B=0 Reference?
Yinzhe Wu, Jiahao Huang, Fanwen Wang +4
Diffusion MRI (dMRI) is essential for studying brain microstructure, but high-resolution imaging remains challenging due to the inherent trade-offs between acquisition time and sig…
OPTIKS: Optimized Gradient Properties Through Timing in K-Space
Matthew A. McCready, Xiaozhi Cao, Kawin Setsompop +2
A customizable method (OPTIKS) for designing fast trajectory-constrained gradient waveforms with optimized time domain properties was developed. Given a specified multidimensional…
Physics-Informed Implicit Neural Representations for Joint B0 Estimation and Echo Planar Imaging
Wenqi Huang, Nan Wang, Congyu Liao +4
Echo Planar Imaging (EPI) is widely used for its rapid acquisition but suffers from severe geometric distortions due to B0 inhomogeneities, particularly along the phase encoding di…
ACE-Net: AutofoCus-Enhanced Convolutional Network for Field Imperfection Estimation with application to high b-value spiral Diffusion MRI
Mengze Gao, Zachary Shah, Xiaozhi Cao +3
Spatiotemporal magnetic field variations from B0-inhomogeneity and diffusion-encoding-induced eddy-currents can be detrimental to rapid image-encoding schemes such as spiral, EPI a…
Compartment-specific estimation of T2 and T2* with diffusion-PEPTIDE MRI
Ting Gong, Merlin J. Fair, Kawin Setsompop +1
We present a microstructure imaging technique for estimating compartment-specific T2 and T2* simultaneously in the human brain. Microstructure imaging with diffusion MRI (dMRI) has…
Accelerating MRI with Longitudinally-informed Latent Posterior Sampling
Yonatan Urman, Zachary Shah, Ashwin Kumar +2
Purpose: To accelerate MRI acquisition by incorporating the previous scans of a subject during reconstruction. Although longitudinal imaging constitutes much of clinical MRI, lever…
Data and Physics driven Deep Learning Models for Fast MRI Reconstruction: Fundamentals and Methodologies
Jiahao Huang, Yinzhe Wu, Fanwen Wang +17
Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric…
An Efficient Algorithm for Spatial-Spectral Partial Volume Compartment Mapping with Applications to Multicomponent Diffusion and Relaxation MRI
Yunsong Liu, Debdut Mandal, Congyu Liao +2
We introduce a new algorithm to solve a regularized spatial-spectral image estimation problem. Our approach is based on the linearized alternating directions method of multipliers…
High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting
Congyu Liao, Xiaozhi Cao, Siddharth Srinivasan Iyer +14
Purpose: This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and pr…
Sequence adaptive field-imperfection estimation (SAFE): retrospective estimation and correction of and inhomogeneities for enhanced MRF quantification
Mengze Gao, Xiaozhi Cao, Daniel Abraham +2
and field-inhomogeneities can significantly reduce accuracy and robustness of MRF's quantitative parameter estimates. Additional and calibration scans c…
Blip-Up Blip-Down Circular EPI (BUDA-cEPI) for Distortion-Free dMRI with Rapid Unrolled Deep Learning Reconstruction
Uten Yarach, Itthi Chatnuntawech, Congyu Liao +9
Purpose: We implemented the blip-up, blip-down circular echo planar imaging (BUDA-cEPI) sequence with readout and phase partial Fourier to reduced off-resonance effect and T2* blur…
Implicit Representation of GRAPPA Kernels for Fast MRI Reconstruction
Daniel Abraham, Mark Nishimura, Xiaozhi Cao +2
MRI data is acquired in Fourier space/k-space. Data acquisition is typically performed on a Cartesian grid in this space to enable the use of a fast Fourier transform algorithm to…
DDM: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
Tiange Xiang, Mahmut Yurt, Ali B Syed +2
Magnetic resonance imaging (MRI) is a common and life-saving medical imaging technique. However, acquiring high signal-to-noise ratio MRI scans requires long scan times, resulting…
Time-efficient, High Resolution 3T Whole Brain Quantitative Relaxometry using 3D-QALAS with Wave-CAIPI Readouts
Jaejin Cho, Borjan Gagoski, Tae Hyung Kim +9
Purpose: Volumetric, high-resolution, quantitative mapping of brain tissue relaxation properties is hindered by long acquisition times and signal-to-noise (SNR) challenges. This st…
Polynomial Preconditioners for Regularized Linear Inverse Problems
Siddharth Srinivasan Iyer, Frank Ong, Xiaozhi Cao +4
This work aims to accelerate the convergence of proximal gradient methods used to solve regularized linear inverse problems. This is achieved by designing a polynomial-based precon…
BUDA-SAGE with self-supervised denoising enables fast, distortion-free, high-resolution T2, T2*, para- and dia-magnetic susceptibility mapping
Zijing Zhang, Long Wang, Jaejin Cho +10
To rapidly obtain high resolution T2, T2* and quantitative susceptibility mapping (QSM) source separation maps with whole-brain coverage and high geometric fidelity. We propose Bli…
Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging
Xiaozhi Cao, Congyu Liao, Siddharth Srinivasan Iyer +10
Purpose: To improve image quality and accelerate the acquisition of 3D MRF. Methods: Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with loca…
eRAKI: Fast Robust Artificial neural networks for K-space Interpolation (RAKI) with Coil Combination and Joint Reconstruction
Heng Yu, Zijing Dong, Yamin Arefeen +3
RAKI can perform database-free MRI reconstruction by training models using only auto-calibration signal (ACS) from each specific scan. As it trains a separate model for each indivi…