PPORLD-EDNetLDCT: A Proximal Policy Optimization-based reinforcement learning framework for adaptive low-dose CT denoising
Low-dose computed tomography (LDCT) is critical for minimizing radiation exposure, but it often leads to increased noise and reduced image quality. Traditional denoising methods, such as iterative optimization or supervised learning, often fail to preserve image quality. To address these challenges, we introduce PPORLD...
Debopom Sutradhar, Ripon Kumar Debnath, Mohaimenul Azam Khan Raiaan et al.
· Biomedical Signal Processing... · 0 citations