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Accelerated MR parametric mapping with a hybrid deep learning model

Accelerating spin-lock imagingusing signal compensated low-rank plus sparse matrix decomposition

Assessment of acquisition strategies of CEST MR fingerprinting pH imaging using Cramer-Rao Bound algorithm

The Comparison of denoising methods for cardiac diffusion tensor imaging

DEMO: Deep MR Parametric Mapping using Unsupervised Multi-tasking Framework

Detection of liver fibrosis in a Rat NASH Model using water specific T1 mapping with Gadoxetic Acid -enhanced MRI

High power RF amplifier for UHF MRI with configurable number of channels

Magnetic resonance thermometry in activated interscapular brown adipose tissue of rats with various dose of norepinephrine

Multi-task MR imaging with deep learning

A novel unsupervised domain adaptation method for deep learning-based prostate MR image segmentation

Author:Cheng Li  Hui Sun  Taohui Xiao  Xin Liu  Hairong Zheng  Shanshan Wang  

Session Type:Digital Poster  

Session Date:Thursday, 20 May 2021  

Topic:Prostate  

Session Name:Prostate: Deep Learning  

Program Number:4109  

Room Session:Concurrent 5  

Institution:Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences  

A Plug-and-play Low-rank Network Modulein Dynamic MR Imaging

PU-NET: A robust phase unwrapping method for magnetic resonance imaging based on deep learning

Rapid MR Parametric Mapping using Deep Learning

Reduced Field of View Parallel Imaging with Wave Encoded k-Space Trajectory

Resolving fold-over artefacts for Reduced Field-of-View Parallel Imaging with Cartesian Sampling

Segmentation of whole-body adipose tissue from magnetic resonance fat-fraction images with U-net deep-learning framework

Unsupervised deep learning for multi-modal MR image registration with topology-preservingdual consistency constraint

VCC-Wave for Improved Parallel MRI of High Resolution and High Bandwidth