Related Experiment Video
Updated: Nov 12, 2025
Point-of-Care Lung Ultrasound in Adults: Image Acquisition
Published on: March 3, 2023
Evaluation of lung involvement in COVID-19 pneumonia based on ultrasound images
Zhaoyu Hu1, Zhenhua Liu2, Yijie Dong2
1Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
Background:
Lung ultrasound (LUS) can be an important imaging tool for the diagnosis and assessment of lung involvement. Ultrasound sonograms have been confirmed to illustrate damage to a person's lungs, which means that the correct classification and scoring of a patient's sonogram can be used to assess lung involvement.
Methods:
The purpose of this study was to establish a lung involvement assessment model based on deep learning. A novel multimodal channel and receptive field attention network combined with ResNeXt (MCRFNet) was proposed to classify sonograms, and the network can automatically fuse shallow features and determine the importance of different channels and respective fields. Finally, sonogram classes were transformed into scores to evaluate lung involvement from the initial diagnosis to rehabilitation.
Results And Conclusion:
Using multicenter and multimodal ultrasound data from 104 patients, the diagnostic model achieved 94.39% accuracy, 82.28% precision, 76.27% sensitivity, and 96.44% specificity. The lung involvement severity and the trend of COVID-19 pneumonia were evaluated quantitatively.
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Published on: December 19, 2020
06:15Protocol and Guidelines for Point-of-Care Lung Ultrasound in Diagnosing Neonatal Pulmonary Diseases Based on International Expert Consensus
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