Application of deep learning reconstruction at prone position chest scanning of early interstitial lung disease
With 63.7% reduction of radiation dose, the overall image quality of LDCT DLR was comparable to HRCT HIR in prone scanning for early ILD patients. This study supported that DLR was promising for maintaining image quality under a lower radiation dose in prone scanning, and it offered valuable insights for the selection of images reconstruction algorithms for the diagnosis and follow-up of early ILD.
Authors
- Lan Song (ORCID: https://orcid.org/0000-0001-6598-6964)
- Ying Ming
- Jiaru Wang (ORCID: https://orcid.org/0009-0003-8089-4111)
- Sirong Piao
- Yinghao Xu
- Ruijie Zhao (ORCID: https://orcid.org/0009-0003-1867-3422)
- Wei Song (ORCID: https://orcid.org/0000-0002-8395-9991)
- Xin Sui (ORCID: https://orcid.org/0000-0001-5267-6115)
- Zixing Wang (ORCID: https://orcid.org/0000-0002-0814-8822)
- Ran Xiao (ORCID: https://orcid.org/0000-0002-1359-4237)
- Zhuangfei Ma
- Yun Wang (ORCID: https://orcid.org/0000-0002-7495-5542)
- Peilin Fan
- Jinhua Wang (ORCID: https://orcid.org/0009-0000-5380-430X)
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- System Equipment (China) (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-08-19
- DOI
- https://doi.org/10.1186/s12880-025-01871-2
- Primary Topic
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Peking Union Medical College Hospital