A deep learning AI model for determining the relationship between X-Ray detectors and patient positioning in chest radiography
The AI model utilizing a customized CNN architecture has demonstrated its potential to automatically detect the positional relationship between the patient and the X-ray detector during chest radiography procedures. This model can potentially alleviate the workload of radiologic technologists in producing chest radiographs and enhance the accuracy of the imaging process.
Authors
- Xiong Wu (ORCID: https://orcid.org/0000-0002-4282-5479)
- Junjiao Hu (ORCID: https://orcid.org/0000-0003-4240-724X)
- Shan Jiang (ORCID: https://orcid.org/0000-0002-5518-5335)
- Haitao Yang (ORCID: https://orcid.org/0000-0002-4987-5794)
- Xiaofan Chen (ORCID: https://orcid.org/0000-0003-1538-7829)
- Bo Jiang (ORCID: https://orcid.org/0009-0000-7143-3733)
- Kai Deng (ORCID: https://orcid.org/0009-0000-2562-6948)
- Weijun Situ (ORCID: https://orcid.org/0009-0001-9749-5745)
Institutions
- Central South University (CN)
- Second Xiangya Hospital of Central South University (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-10-13
- DOI
- https://doi.org/10.1371/journal.pone.0333209
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00