20 citations · 42 across the 6 of their papers we have counts for
6 papers
Accurate parameter estimation using scan-specific unsupervised deep learning for relaxometry and MR fingerprinting
Mengze Gao, Huihui Ye, Tae Hyung Kim +3
We propose an unsupervised convolutional neural network (CNN) for relaxation parameter estimation. This network incorporates signal relaxation and Bloch simulations while taking ad…
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…
Highly Accelerated EPI with Wave Encoding and Multi-shot Simultaneous Multi-Slice Imaging
Jaejin Cho, Congyu Liao, Qiyuan Tian +8
We introduce wave encoded acquisition and reconstruction techniques for highly accelerated echo planar imaging (EPI) with reduced g-factor penalty and image artifacts. Wave-EPI inv…
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…
Efficient T2 mapping with Blip-up/down EPI and gSlider-SMS (T2-BUDA-gSlider)
Xiaozhi Cao, Congyu Liao, Zijing Zhang +7
Purpose: To rapidly obtain high isotropic-resolution T2 maps with whole-brain coverage and high geometric fidelity. Methods: A T2 blip-up/down echo planar imaging (EPI) acquisition…
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…