Unsharp structure guided filtering for self-supervised low-dose CT imaging
Q Wu, X Ji, Y Gu, J Xiang, G Quan, B Li… - … on Medical Imaging, 2023 - ieeexplore.ieee.org
Low-dose computed tomography (LDCT) imaging faces great challenges. Although
supervised learning has revealed great potential, it requires sufficient and high-quality …
supervised learning has revealed great potential, it requires sufficient and high-quality …
Unsupervised and Self-supervised Learning in Low-Dose Computed Tomography Denoising: Insights from Training Strategies
F Zhao, M Liu, M Xiang, D Li, X Jiang, X Jin… - Journal of Imaging …, 2024 - Springer
In recent years, X-ray low-dose computed tomography (LDCT) has garnered widespread
attention due to its significant reduction in the risk of patient radiation exposure. However …
attention due to its significant reduction in the risk of patient radiation exposure. However …
SVB: Self-supervised Real CT Denoising via Similarity-based Visual Blind-spot Scheme
Y Wang, S Wang, A Cai, K An, N Liang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Low-dose and photon-counting computed tomography (CT) denoising is a challenging task
in medical imaging that has attracted significant attention. The supervised deep denoising …
in medical imaging that has attracted significant attention. The supervised deep denoising …