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eess.IV2022★ 2 cited
SRNR: Training neural networks for Super-Resolution MRI using Noisy high-resolution Reference data
Jiaxin Xiao, Zihan Li, Berkin Bilgic +3
Neural network (NN) based approaches for super-resolution MRI typically require high-SNR high-resolution reference data acquired in many subjects, which is time consuming and a bar…
eess.IV2021
SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI
Qiyuan Tian, Ziyu Li, Qiuyun Fan +4
The noise in diffusion-weighted images (DWIs) decreases the accuracy and precision of diffusion tensor magnetic resonance imaging (DTI) derived microstructural parameters and leads…
eess.IV2021★ 3 cited
SRDTI: Deep learning-based super-resolution for diffusion tensor MRI
Qiyuan Tian, Ziyu Li, Qiuyun Fan +8
High-resolution diffusion tensor imaging (DTI) is beneficial for probing tissue microstructure in fine neuroanatomical structures, but long scan times and limited signal-to-noise r…