Exploring the Utility of Self-Supervised Pretraining Strategies for the Detection of Absent Lung Sliding in M-Mode Lung Ultrasound

Author:

VanBerlo Blake1,Li Brian1,Wong Alexander1,Hoey Jesse1,Arntfield Robert2

Affiliation:

1. University of Waterloo

2. Western University

Publisher

IEEE

Reference28 articles.

1. Detecting the absence of lung sliding in lung ultrasounds using deep learning;jaš?ur;Applied Sciences,2021

2. Momentum contrast for unsupervised visual representation learning;he;Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,2020

3. Whole Body Ultrasonography in the Critically Ill

4. Self-Supervised Representation Learning for Ultrasound Video

5. Bootstrap your own latent-a new approach to self-supervised learning;grill;Advances in neural information processing systems,2020

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