1 code implementation • 25 Nov 2022 • Bing Guan, Cailian Yang, Liu Zhang, Shanzhou Niu, Minghui Zhang, Yuhao Wang, Weiwen Wu, Qiegen Liu
When the number of projection view changes, the DL network should be retrained with updated sparse-view/full-view CT image pairs.
no code implementations • 19 Jan 2022 • Cailian Yang, Xianghao Liao, Yuhao Wang, Minghui Zhang, Qiegen Liu
Two main components are incorporated into the network design, namely variable augmentation technology and sum of squares (SOS) objective function.
1 code implementation • 2 Sep 2021 • Yuhao Wang, Ruirui Liu, Zihao Li, Cailian Yang, Qiegen Liu
As an effective way to integrate the information contained in multiple medical images under different modalities, medical image synthesis and fusion have emerged in various clinical applications such as disease diagnosis and treatment planning.
1 code implementation • 14 Aug 2021 • Kai Hong, CHUNHUA WU, Cailian Yang, Minghui Zhang, Yancheng Lu, Yuhao Wang, Qiegen Liu
This work presents an unsupervised deep learning scheme that exploiting high-dimensional assisted score-based generative model for color image restoration tasks.
6 code implementations • 28 Dec 2020 • Kai Hong, Jin Li, Wanyun Li, Cailian Yang, Minghui Zhang, Yuhao Wang, Qiegen Liu
Furthermore, the joint intensity-gradient constraint in data-fidelity term is proposed to limit the degree of freedom within generative model at the iterative colorization stage, and it is conducive to edge-preserving.