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)...
share
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
∙
02/17/2021
SRDTI: Deep learning-based super-resolution for diffusion tensor MRI
High-resolution diffusion tensor imaging (DTI) is beneficial for probing...
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
∙
05/30/2016
