The proposed networks may be readily applied to other image processing tasks including image reconstruction, image deblurring, and image super-resolution.
Apr 28, 2023 · We propose a novel degradation adaption local-to-global transformer (DALG-Transformer) for restoring the LDCT image.
A novel degradation adaption local-to-global transformer (DALG-Transformer) for restoring the LDCT image, built on self-attention modules which excel at ...
Degradation Adaption Local-to-Global Transformer for Low-Dose CT Image Denoising. April 2023; Journal of Digital Imaging 36(22). DOI:10.1007/s10278-023-00831-y.
Degradation Adaption Local-to-Global Transformer for Low-Dose CT Image Denoising. https://doi.org/10.1007/s10278-023-00831-y.
考虑到患者暴露于X射线辐射的潜在风险，低剂量CT（LDCT）图像已广泛应用于医学成像领域。由于减少辐射剂量可能会导致噪声和伪影增加，因此在过去几十年中消除LDCT 图像中的 ...
Degradation Adaption Local-to-Global Transformer for Low-Dose CT Image Denoising. Wang H, Chi J, Wu C, Yu X, Wu H. J Digit Imaging; 2023 Aug; 36(4):1894-1909.
This paper investigates and evaluates some top deep learning models proposed in the field of low-dose image denoising in recent years.
DSAT is used to extract the global and local information of fused features to improve denoising. Abstract. Low-Dose Computed Tomography (LDCT) image denoising ...
Missing: Degradation Adaption
Degradation Adaption Local-to-Global Transformer for Low-Dose CT Image Denoising. Huan Wang; Jianning Chi; Hao Wu. Original Paper 28 April 2023 Pages: 1894 ...