research
∙
08/09/2023
Improved Multi-Shot Diffusion-Weighted MRI with Zero-Shot Self-Supervised Learning Reconstruction
Diffusion MRI is commonly performed using echo-planar imaging (EPI) due ...
share
research
∙
02/25/2022
High-Dimensional Sparse Bayesian Learning without Covariance Matrices
Sparse Bayesian learning (SBL) is a powerful framework for tackling the ...
research
∙
02/06/2022
Wave-Encoded Model-based Deep Learning for Highly Accelerated Imaging with Joint Reconstruction
Purpose: To propose a wave-encoded model-based deep learning (wave-MoDL)...
research
∙
12/07/2021
Accurate parameter estimation using scan-specific unsupervised deep learning for relaxometry and MR fingerprinting
We propose an unsupervised convolutional neural network (CNN) for relaxa...
research
∙
12/02/2021
Quantifying the uncertainty of neural networks using Monte Carlo dropout for deep learning based quantitative MRI
Dropout is conventionally used during the training phase as regularizati...
research
∙
11/14/2021
SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI
The noise in diffusion-weighted images (DWIs) decreases the accuracy and...
research
∙
05/21/2021
Covariance-Free Sparse Bayesian Learning
Sparse Bayesian learning (SBL) is a powerful framework for tackling the ...
research
∙
04/02/2021
Scan Specific Artifact Reduction in K-space (SPARK) Neural Networks Synergize with Physics-based Reconstruction to Accelerate MRI
Purpose: To develop a scan-specific model that estimates and corrects k-...
research
∙
02/17/2021
SRDTI: Deep learning-based super-resolution for diffusion tensor MRI
High-resolution diffusion tensor imaging (DTI) is beneficial for probing...
research
∙
09/30/2019
Nonlinear Dipole Inversion (NDI) enables Quantitative Susceptibility Mapping (QSM) without parameter tuning
We propose Nonlinear Dipole Inversion (NDI) for high-quality Quantitativ...
research
∙
08/08/2018
Highly Accelerated Multishot EPI through Synergistic Combination of Machine Learning and Joint Reconstruction
Purpose: To introduce a combined machine learning (ML) and physics-based...
research
∙
05/29/2018
Rice Classification Using Spatio-Spectral Deep Convolutional Neural Network
Rice has been one of the staple foods that contribute significantly to h...
research
∙
05/29/2018