14 citations · 16 across the 6 of their papers we have counts for
8 papers · 1 filter
Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRI
Zi Wang, Min Xiao, Yirong Zhou +13
Dynamic magnetic resonance imaging (MRI) plays an indispensable role in cardiac diagnosis. To enable fast imaging, the k-space data can be undersampled but the image reconstruction…
Cloud-Magnetic Resonance Imaging System: In the Era of 6G and Artificial Intelligence
Yirong Zhou, Yanhuang Wu, Yuhan Su +5
Magnetic Resonance Imaging (MRI) plays an important role in medical diagnosis, generating petabytes of image data annually in large hospitals. This voluminous data stream requires…
Bloch Equation Enables Physics-informed Neural Network in Parametric Magnetic Resonance Imaging
Qingrui Cai, Liuhong Zhu, Jianjun Zhou +3
Magnetic resonance imaging (MRI) is an important non-invasive imaging method in clinical diagnosis. Beyond the common image structures, parametric imaging can provide the intrinsic…
One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction
Zi Wang, Xiaotong Yu, Chengyan Wang +25
Magnetic resonance imaging (MRI) is a widely used radiological modality renowned for its radiation-free, comprehensive insights into the human body, facilitating medical diagnoses.…
Accelerated MRI Reconstruction with Separable and Enhanced Low-Rank Hankel Regularization
Xinlin Zhang, Hengfa Lu, Di Guo +5
The combination of the sparse sampling and the low-rank structured matrix reconstruction has shown promising performance, enabling a significant reduction of the magnetic resonance…
XCloud-pFISTA: A Medical Intelligence Cloud for Accelerated MRI
Yirong Zhou, Chen Qian, Yi Guo +6
Machine learning and artificial intelligence have shown remarkable performance in accelerated magnetic resonance imaging (MRI). Cloud computing technologies have great advantages i…