Comparative evaluation of deep learning-based and conventional reconstruction techniques for image quality enhancement in low-dose chest computed tomography
The proposed DL method provided better image quality than did the mainstream IR methods in low-dose chest CT images. This novel DL technique could be effective and practicable for significantly reducing radiation dose while ensuring the quality of clinical diagnostic images in routine radiology work.
Authors
- Xianfeng Yang (ORCID: https://orcid.org/0000-0002-9416-6882)
- Romaric Loffroy (ORCID: https://orcid.org/0000-0002-3107-5967)
- Shan Lei (ORCID: https://orcid.org/0000-0002-4133-1389)
- Shujuan Zhou (ORCID: https://orcid.org/0000-0003-3809-7613)
- Zhengyu Zhang (ORCID: https://orcid.org/0000-0002-8385-4890)
- Chong Liu (ORCID: https://orcid.org/0000-0001-9521-2740)
- Hae Won Kim (ORCID: https://orcid.org/0000-0002-6707-3904)
Institutions
- Soochow University (CN)
- First Affiliated Hospital of Soochow University (CN)
- Keimyung University (KR)
Publication Details
- Journal
- Journal of Thoracic Disease
- Published
- 2025-05-01
- DOI
- https://doi.org/10.21037/jtd-2025-589
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00