An effective sinogram inpainting for complementary limited-angle dual-energy computed tomography imaging using generative adversarial networks.

In conclusion, both qualitative and quantitative comparison and analysis demonstrate that our proposed method achieves a good artifact suppression effect and can suitably solve the complementary limited-angle problem. PMID: 33104055 [PubMed - as supplied by publisher]

https://www.ncbi.nlm.nih.gov/pubmed/33104055?dopt=Abstract

Source: Journal of X-Ray Science and Technology - October 28, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research