no code implementations • 22 Mar 2023 • Wenjun Xia, Hsin Wu Tseng, Chuang Niu, Wenxiang Cong, Xiaohua Zhang, Shaohua Liu, Ruola Ning, Srinivasan Vedantham, Ge Wang
Specifically, in this study we transform the cutting-edge Denoising Diffusion Probabilistic Model (DDPM) into a parallel framework for sub-volume-based sparse-view breast CT image reconstruction in projection and image domains.
1 code implementation • 9 Dec 2019 • Huidong Xie, Hongming Shan, Wenxiang Cong, Chi Liu, Xiaohua Zhang, Shaohua Liu, Ruola Ning, Ge Wang
Breast CT provides image volumes with isotropic resolution in high contrast, enabling detection of small calcification (down to a few hundred microns in size) and subtle density differences.
no code implementations • 25 Sep 2019 • Wenxiang Cong, Hongming Shan, Xiaohua Zhang, Shaohua Liu, Ruola Ning, Ge Wang
In this study, we propose a deep-learning-based method to establish a residual neural network model for the image reconstruction, which is applied for few-view breast CT to produce high quality breast CT images.
no code implementations • 2 Jul 2019 • Huidong Xie, Hongming Shan, Wenxiang Cong, Xiaohua Zhang, Shaohua Liu, Ruola Ning, Ge Wang
Few-view CT image reconstruction is an important topic to reduce the radiation dose.