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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…
AID-DTI: Accelerating High-fidelity Diffusion Tensor Imaging with Detail-preserving Model-based Deep Learning
Wenxin Fan, Jian Cheng, Cheng Li +4
Deep learning has shown great potential in accelerating diffusion tensor imaging (DTI). Nevertheless, existing methods tend to suffer from Rician noise and eddy current, leading to…
CSR-dMRI: Continuous Super-Resolution of Diffusion MRI with Anatomical Structure-assisted Implicit Neural Representation Learning
Ruoyou Wu, Jian Cheng, Cheng Li +5
Deep learning-based dMRI super-resolution methods can effectively enhance image resolution by leveraging the learning capabilities of neural networks on large datasets. However, th…
Rethinking the optimization process for self-supervised model-driven MRI reconstruction
Weijian Huang, Cheng Li, Wenxin Fan +4
Recovering high-quality images from undersampled measurements is critical for accelerated MRI reconstruction. Recently, various supervised deep learning-based MRI reconstruction me…