5 citations · 8 across the 4 of their papers we have counts for
10 papers
SRDTI: Deep learning-based super-resolution for diffusion tensor MRI
Qiyuan Tian, Ziyu Li, Qiuyun Fan +8
High-resolution diffusion tensor imaging (DTI) is beneficial for probing tissue microstructure in fine neuroanatomical structures, but long scan times and limited signal-to-noise r…
Scan-specific, Parameter-free Artifact Reduction in K-space (SPARK)
Onur Beker, Congyu Liao, Jaejin Cho +3
We propose a convolutional neural network (CNN) approach that works synergistically with physics-based reconstruction methods to reduce artifacts in accelerated MRI. Given reconstr…
Echo Planar Time-Resolved Imaging (EPTI) with Subspace Reconstruction and Optimized Spatiotemporal Encoding
Zijing Dong, Fuyixue Wang, Timothy G. Reese +2
Purpose: To develop new encoding and reconstruction techniques for fast multi-contrast quantitative imaging. Methods: The recently proposed Echo Planar Time-resolved Imaging (EPTI)…
Joint multi-contrast Variational Network reconstruction (jVN) with application to rapid 2D and 3D imaging
Daniel Polak, Stephen Cauley, Berkin Bilgic +4
Purpose: To improve the image quality of highly accelerated multi-channel MRI data by learning a joint variational network that reconstructs multiple clinical contrasts jointly. Me…
Nonlinear Dipole Inversion (NDI) enables Quantitative Susceptibility Mapping (QSM) without parameter tuning
Daniel Polak, Itthi Chatnuntawech, Jaeyeon Yoon +6
We propose Nonlinear Dipole Inversion (NDI) for high-quality Quantitative Susceptibility Mapping (QSM) without regularization tuning, while matching the image quality of state-of-t…
Highly efficient MRI through multi-shot echo planar imaging
Congyu Liao, Xiaozhi Cao, Jaejin Cho +3
Multi-shot echo planar imaging (msEPI) is a promising approach to achieve high in-plane resolution with high sampling efficiency and low T2* blurring. However, due to the geometric…