52 citations · 56 across the 5 of their papers we have counts for
5 papers
Towards Modality- and Sampling-Universal Learning Strategies for Accelerating Cardiovascular Imaging: Summary of the CMRxRecon2024 Challenge
Fanwen Wang, Zi Wang, Yan Li +60
Cardiovascular health is vital to human well-being, and cardiac magnetic resonance (CMR) imaging is considered the {clinical reference standard} for diagnosing cardiovascular disea…
Exponential Signal Reconstruction with Deep Hankel Matrix Factorization
Yihui Huang, Jinkui Zhao, Zi Wang +3
Exponential is a basic signal form, and how to fast acquire this signal is one of the fundamental problems and frontiers in signal processing. To achieve this goal, partial data ma…
An auto-parameter denoising method for nuclear magnetic resonance spectroscopy based on low-rank Hankel matrix
Tianyu Qiu, Wenjing Liao, Di Guo +4
Nuclear Magnetic Resonance (NMR) spectroscopy, which is modeled as the sum of damped exponential signals, has become an indispensable tool in various scenarios, such as the structu…
pISTA-SENSE-ResNet for Parallel MRI Reconstruction
Tieyuan Lu, Xinlin Zhang, Yihui Huang +6
Magnetic resonance imaging has been widely applied in clinical diagnosis, however, is limited by its long data acquisition time. Although imaging can be accelerated by sparse sampl…
A Guaranteed Convergence Analysis for the Projected Fast Iterative Soft-Thresholding Algorithm in Parallel MRI
Xinlin Zhang, Hengfa Lu, Di Guo +4
The boom of non-uniform sampling and compressed sensing techniques dramatically alleviates the lengthy data acquisition problem of magnetic resonance imaging. Sparse reconstruction…