Towards full-stack deep learning-empowered data processing pipeline for synchrotron tomography experiments
Z Zhang, C Li, W Wang, Z Dong, G Liu, Y Dong… - The Innovation, 2023 - Elsevier
Synchrotron tomography experiments are transitioning into multi-functional, cross-scale and
dynamic characterizations, enabled by new generation synchrotron light sources and fast …
dynamic characterizations, enabled by new generation synchrotron light sources and fast …
A dual-domain diffusion model for sparse-view ct reconstruction
To reduce the radiation dose, sparse-view computed tomography (CT) reconstruction has
been proposed, aiming to recover high-quality CT images from sparsely sampled sinogram …
been proposed, aiming to recover high-quality CT images from sparsely sampled sinogram …
[HTML][HTML] A systematic literature review: deep learning techniques for synthetic medical image generation and their applications in radiotherapy
MK Sherwani, S Gopalakrishnan - Frontiers in Radiology, 2024 - frontiersin.org
The aim of this systematic review is to determine whether Deep Learning (DL) algorithms
can provide a clinically feasible alternative to classic algorithms for synthetic Computer …
can provide a clinically feasible alternative to classic algorithms for synthetic Computer …
A dense and U-shaped transformer with dual-domain multi-loss function for sparse-view CT reconstruction
P Liu, C Fang, Z Qiao - Journal of X-Ray Science and …, 2024 - content.iospress.com
OBJECTIVE: CT image reconstruction from sparse-view projections is an important imaging
configuration for low-dose CT, as it can reduce radiation dose. However, the CT images …
configuration for low-dose CT, as it can reduce radiation dose. However, the CT images …