One-Sample Diffusion Modeling in Projection Domain for Low-Dose CT Imaging
B Huang, S Lu, L Zhang, B Lin, W Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Low-dose computed tomography (CT) is crucial in clinical applications for reducing radiation
risks. However, lowering the radiation dose will significantly degrade the image quality. In …
risks. However, lowering the radiation dose will significantly degrade the image quality. In …
Conversion of the Mayo LDCT data to synthetic equivalent through the diffusion model for training denoising networks with a theoretically perfect privacy
Deep learning techniques are widely used in the medical imaging field; for example, low-
dose CT denoising. However, all these methods usually require a large number of data …
dose CT denoising. However, all these methods usually require a large number of data …
Pre-trained Diffusion Models for Plug-and-Play Medical Image Enhancement
Deep learning-based medical image enhancement methods (eg, denoising and super-
resolution) mainly rely on paired data and correspondingly the well-trained models can only …
resolution) mainly rely on paired data and correspondingly the well-trained models can only …
Diffusion X-ray image denoising
X-ray imaging is a cornerstone in medical diagnosis, constituting a significant portion of the
radiation dose encountered by patients. Excessive radiation poses health risks, particularly …
radiation dose encountered by patients. Excessive radiation poses health risks, particularly …
Diffusion Denoising for Low-Dose-CT Model
R Li - arXiv preprint arXiv:2301.11482, 2023 - arxiv.org
Low-dose Computed Tomography (LDCT) reconstruction is an important task in medical
image analysis. Recent years have seen many deep learning based methods, proved to be …
image analysis. Recent years have seen many deep learning based methods, proved to be …