16 citations · 19 across the 5 of their papers we have counts for
5 papers
Accelerated MR Fingerprinting with Low-Rank and Generative Subspace Modeling
Hengfa Lu, Huihui Ye, Lawrence L. Wald +1
Magnetic Resonance (MR) Fingerprinting is an emerging multi-parametric quantitative MR imaging technique, for which image reconstruction methods utilizing low-rank and subspace con…
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…
Accelerated MRI Reconstruction with Separable and Enhanced Low-Rank Hankel Regularization
Xinlin Zhang, Hengfa Lu, Di Guo +5
The combination of the sparse sampling and the low-rank structured matrix reconstruction has shown promising performance, enabling a significant reduction of the magnetic resonance…
Ultrashort Echo Time Magnetic Resonance Fingerprinting (UTE-MRF) for Simultaneous Quantification of Long and Ultrashort T2 Tissues
Qing Li, Xiaozhi Cao, Huihui Ye +3
Purpose: To demonstrate an ultrashort echo time magnetic resonance fingerprinting (UTE-MRF) method that can simultaneously quantify tissue relaxometries for muscle and bone in musc…