Standalone electrical impedance tomography predicts spirometry indicators and enables regional lung assessment

Author:

Zouari Fedi1,Oon Wei Yi1,Modak Dipyaman1,Kwok Wang Chun2,Cao Peng3,Lee Wei-Ning4,Tam Terence Chi Chun2,Wong Eddie C.1,Chan Russell W.1

Affiliation:

1. Gense Technologies Ltd.,Hong Kong,China

2. Queen Mary Hospital,Department of Medicine,Hong Kong,China

3. The University of Hong Kong,Li Ka Shing Faculty of Medicine,Department of Diagnostic Radiology,Hong Kong,China

4. The University of Hong Kong,Faculty of Engineering,Department of Electrical and Electronic Engineering,Hong Kong,China

Publisher

IEEE

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Spatio-Temporal Classification of Lung Ventilation Patterns Using 3D EIT Images: A General Approach for Individualized Lung Function Evaluation;IEEE Journal of Biomedical and Health Informatics;2024-01

2. CycleGAN with mutual information loss constraint generates structurally aligned CT images from functional EIT images;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24

3. Electric impedance tomography enables portable and non-invasive approach to screen and monitor chronic kidney disease;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24

4. Deep learning based reconstruction enables high-resolution electrical impedance tomography for lung function assessment;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24

5. Global and regional lung function assessment using portable electrical impedance tomography (EIT) system: clinical study;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24

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