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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
Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction
Chenglong Ma, Zilong Li, Yuanlin Li +5
Metal artifacts in computed tomography (CT) images can significantly degrade image quality and impede accurate diagnosis. Supervised metal artifact reduction (MAR) methods, trained…