3 papers
eess.IV2025
Noise-Inspired Diffusion Model for Generalizable Low-Dose CT Reconstruction
Qi Gao, Zhihao Chen, Dong Zeng +3
The generalization of deep learning-based low-dose computed tomography (CT) reconstruction models to doses unseen in the training data is important and remains challenging. Previou…
eess.IV2025
Continuous Filtered Backprojection by Learnable Interpolation Network
Hui Lin, Dong Zeng, Qi Xie +3
Accurate reconstruction of computed tomography (CT) images is crucial in medical imaging field. However, there are unavoidable interpolation errors in the backprojection step of th…
eess.IV2024
SS-CTML: Self-Supervised Cross-Task Mutual Learning for CT Image Reconstruction
Gaofeng Chen, Yaoduo Zhang, Li Huang +5
Supervised deep-learning (SDL) techniques with paired training datasets have been widely studied for X-ray computed tomography (CT) image reconstruction. However, due to the diffic…