no code implementations • 2 Aug 2023 • Zejun Wu, Jiechao Wang, Zunquan Chen, Qinqin Yang, Zhen Xing, Dairong Cao, Jianfeng Bao, Taishan Kang, Jianzhong Lin, Shuhui Cai, Zhong Chen, Congbo Cai
Significance: FlexDTI can well learn diffusion gradient direction information to achieve generalized DTI reconstruction with flexible diffusion gradient scheme.
no code implementations • 19 Oct 2022 • Haitao Huang, Qinqin Yang, Jiechao Wang, Pujie Zhang, Shuhui Cai, Congbo Cai
Significance: As a proof-of-concept work, Simu-Net shows the potential to apply deep learning for rapidly approximating the forward physical process of MRI and may increase the efficiency of Bloch simulation for optimization of MRI pulse sequences and deep learning-based methods.
1 code implementation • 30 Jul 2021 • Qinqin Yang, Yanhong Lin, Jiechao Wang, Jianfeng Bao, Xiaoyin Wang, Lingceng Ma, Zihan Zhou, Qizhi Yang, Shuhui Cai, Hongjian He, Congbo Cai, Jiyang Dong, Jingliang Cheng, Zhong Chen, Jianhui Zhong
Use of synthetic data has provided a potential solution for addressing unavailable or insufficient training samples in deep learning-based magnetic resonance imaging (MRI).
no code implementations • 17 Aug 2017 • Congbo Cai, Yiqing Zeng, Chao Wang, Shuhui Cai, Jun Zhang, Zhong Chen, Xinghao Ding, Jianhui Zhong
After the ResNet was trained, it was applied to reconstruct the T2 mapping from simulation and in vivo human brain data.