COVID-19 feature detection with deep neural networks trained on simulated lung ultrasound B-mode images-Reference-Cited by-同舟云学术

COVID-19 feature detection with deep neural networks trained on simulated lung ultrasound B-mode images

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Ultrasonics Symposium (IUS)
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Author:

Zhao Lingyi¹,Fong Tiffany Clair²,Bell Muyinatu A. Lediju¹

Affiliation:

1. Johns Hopkins University,Department of Electrical and Computer Engineering,Baltimore,MD

2. Johns Hopkins Medicine,Department of Emergency Medicine,Baltimore,MD

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9957114/9957143/09958899.pdf?arnumber=9958899

Reference19 articles.

1. Improved Automatic Bone Segmentation Using Large-Scale Simulated Ultrasound Data to Segment Real Ultrasound Bone Surface Data

2. Unsupervised domain adaptation method for segmenting cross-sectional CCA images

3. Deep Learning to Obtain Simultaneous Image and Segmentation Outputs From a Single Input of Raw Ultrasound Channel Data

4. Generalization of a deep learning network for beamforming and seg-mentation of ultrasound images;seoni;2021 IEEE International Ultrasonics Symposium (IUS),2021

5. Multi-stage investigation of deep neural networks for COVID-19 B-line feature detection in simulated and in vivo ultrasound images

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1. Deep learning for real-time multi-class segmentation of artefacts in lung ultrasound;Ultrasonics;2024-05

2. Detection of COVID-19 features in lung ultrasound images using deep neural networks;Communications Medicine;2024-03-11

3. Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound;IEEE Journal of Biomedical and Health Informatics;2023-09