5 papers
DeepMpMRI: Tensor-decomposition Regularized Learning for Fast and High-Fidelity Multi-Parametric Microstructural MR Imaging
Wenxin Fan, Jian Cheng, Qiyuan Tian +4
Deep learning has emerged as a promising approach for learning the nonlinear mapping between diffusion-weighted MR images and tissue parameters, which enables automatic and deep un…
3D Anatomical Structure-guided Deep Learning for Accurate Diffusion Microstructure Imaging
Xinrui Ma, Jian Cheng, Wenxin Fan +3
Diffusion magnetic resonance imaging (dMRI) is a crucial non-invasive technique for exploring the microstructure of the living human brain. Traditional hand-crafted and model-based…
Spatial-Angular Representation Learning for High-Fidelity Continuous Super-Resolution in Diffusion MRI
Ruoyou Wu, Jian Cheng, Cheng Li +5
Diffusion magnetic resonance imaging (dMRI) often suffers from low spatial and angular resolution due to inherent limitations in imaging hardware and system noise, adversely affect…
Diff5T: Benchmarking Human Brain Diffusion MRI with an Extensive 5.0 Tesla K-Space and Spatial Dataset
Shanshan Wang, Shoujun Yu, Jian Cheng +14
Diffusion magnetic resonance imaging (dMRI) provides critical insights into the microstructural and connectional organization of the human brain. However, the availability of high-…
SamRobNODDI: Q-Space Sampling-Augmented Continuous Representation Learning for Robust and Generalized NODDI
Taohui Xiao, Jian Cheng, Wenxin Fan +3
Neurite Orientation Dispersion and Density Imaging (NODDI) microstructure estimation from diffusion magnetic resonance imaging (dMRI) is of great significance for the discovery and…