32 citations · 95 across the 33 of their papers we have counts for
7 papers · 1 filter
An Unsupervised Deep Learning Method for Multi-coil Cine MRI
Ziwen Ke, Jing Cheng, Leslie Ying +3
Deep learning has achieved good success in cardiac magnetic resonance imaging (MRI) reconstruction, in which convolutional neural networks (CNNs) learn a mapping from the undersamp…
Model Learning: Primal Dual Networks for Fast MR imaging
Jing Cheng, Haifeng Wang, Leslie Ying +1
Magnetic resonance imaging (MRI) is known to be a slow imaging modality and undersampling in k-space has been used to increase the imaging speed. However, image reconstruction from…
Model-based Deep Medical Imaging: the roadmap of generalizing iterative reconstruction model using deep learning
Jing Cheng, Haifeng Wang, Yanjie Zhu +10
Medical imaging is playing a more and more important role in clinics. However, there are several issues in different imaging modalities such as slow imaging speed in MRI, radiation…
Accelerating MR Imaging via Deep Chambolle-Pock Network
Haifeng Wang, Jing Cheng, Sen Jia +8
Compressed sensing (CS) has been introduced to accelerate data acquisition in MR Imaging. However, CS-MRI methods suffer from detail loss with large acceleration and complicated pa…
T1rho Fractional-order Relaxation of Human Articular Cartilage
Lixian Zou, Haifeng Wang, Yanjie Zhu +8
T1rho imaging is a promising non-invasive diagnostic tool for early detection of articular cartilage degeneration. A mono-exponential model is normally used to describe the T1rho r…
Application of Time-Fractional Order Bloch Equation in Magnetic Resonance Fingerprinting
Haifeng Wang, Lixian Zou, Huihui Ye +4
Magnetic resonance fingerprinting (MRF) is one novel fast quantitative imaging framework for simultaneous quantification of multiple parameters with pseudo-randomized acquisition p…
Fast Calculation Method of Average g-Factor for Wave-CAIPI Imaging
Haifeng Wang, Zhilang Qiu, Shi Su +2
Wave-CAIPI MR imaging is a 3D imaging technique which can uniformize the g-factor maps and significantly reduce g-factor penalty at high acceleration factors. But it is time-consum…