The Identification and Severity Staging of Chronic Obstructive Pulmonary Disease Using Quantitative CT Parameters, Radiomics Features, and Deep Learning Features
This biphasic CT-based multimodal approach integrating QCT, radiomics, or DL features offers a clinically valuable tool for COPD identification and severity staging.
Authors
- Wenxiu Zhang (ORCID: https://orcid.org/0000-0001-9962-1998)
- Yuqiong Yang (ORCID: https://orcid.org/0000-0002-6907-592X)
- Shengchuan Feng (ORCID: https://orcid.org/0000-0003-4287-2977)
- Chengyu Miao (ORCID: https://orcid.org/0009-0002-3169-5397)
- Kai Yang (ORCID: https://orcid.org/0000-0003-1923-2859)
- Xiaoyun Liang (ORCID: https://orcid.org/0000-0002-1851-3408)
- Zhenyu Liang (ORCID: https://orcid.org/0000-0002-8746-315X)
- Zizheng Chen
- Yuting Chen (ORCID: https://orcid.org/0000-0001-7767-3957)
- Fengyan Wang (ORCID: https://orcid.org/0000-0001-5737-0625)
- Ran Zhang (ORCID: https://orcid.org/0000-0003-3376-6945)
- Rongchang Chen (ORCID: https://orcid.org/0000-0002-2396-3702)
- Qing Yao (ORCID: https://orcid.org/0009-0002-0015-0407)
- Cuixia Liang
- Huijun Zhao (ORCID: https://orcid.org/0000-0002-8624-4238)
- Qing Xuan Liang (ORCID: https://orcid.org/0009-0006-5822-261X)
Institutions
- Mianyang Third People's Hospital (CN)
- First Affiliated Hospital of Guangzhou Medical University (CN)
- National Institute of Public Health (LA)
- Neusoft (China) (CN)
- Southern Medical University Shenzhen Hospital (CN)
- Shenzhen Second People's Hospital (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Respiration
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1159/000548595
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72