학술논문

Automatically Scoring Lung Ultrasound Videos of COVID-19 and post-COVID-19 Patients
Document Type
Conference
Source
2022 IEEE International Ultrasonics Symposium (IUS) Ultrasonics Symposium (IUS), 2022 IEEE International. :1-4 Oct, 2022
Subject
Bioengineering
Fields, Waves and Electromagnetics
Signal Processing and Analysis
COVID-19
Visualization
Ultrasonic imaging
Pulmonary diseases
Lung
Imaging
Reproducibility of results
Artificial intelligence
deep learning
lung ultrasound
post-COVID-19
Language
ISSN
1948-5727
Abstract
Lung ultrasound (LUS) imaging is playing an important role in the current pandemic, allowing the evaluation of patients affected by COVID-19 pneumonia. However, LUS is limited to the visual inspection of ultrasound data, which negatively affects the reproducibility and reliability of the findings. For these reasons, we were the first to propose a standardized imaging protocol and a scoring system, from which we developed the first artificial intelligence (AI) models able to evaluate LUS videos. Furthermore, we demonstrated prognostic value of our approach and its utility for patients' stratification. In this study, we report on the level of agreement between AI and LUS clinical experts (MD) on LUS data acquired from both COVID-19 patients and post-COVID-19 patients.