53 citations · 348 across the 45 of their papers we have counts for
10 papers · 1 filter
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…
Improving accuracy and uncertainty quantification of deep learning based quantitative MRI using Monte Carlo dropout
Mehmet Yigit Avci, Ziyu Li, Qiuyun Fan +3
Dropout is conventionally used during the training phase as regularization method and for quantifying uncertainty in deep learning. We propose to use dropout during training as wel…
SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI
Qiyuan Tian, Ziyu Li, Qiuyun Fan +4
The noise in diffusion-weighted images (DWIs) decreases the accuracy and precision of diffusion tensor magnetic resonance imaging (DTI) derived microstructural parameters and leads…
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…
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…
Covariance-Free Sparse Bayesian Learning
Alexander Lin, Andrew H. Song, Berkin Bilgic +1
Sparse Bayesian learning (SBL) is a powerful framework for tackling the sparse coding problem while also providing uncertainty quantification. The most popular inference algorithms…
Wave-encoding and Shuffling Enables Rapid Time Resolved Structural Imaging
Siddharth Iyer, Daniel Polak, Congyu Liao +6
T2-Shuffling reconstructs multiple sharp T2-weighted images from a single volumetric fast spin-echo (3D-FSE) scan. Wave-CAIPI is a parallel imaging technique that achieves good rec…
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…