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Development of a Video Laryngoscope with AI Assisted Epiglottis Bounding and Automatic Recording

Stillman, Carson
Abstract
This thesis puts forward a new Convolutional Neural Network based on the U-Net Architecture, called glottisnet to identify the glottis region in the throat. Success was had in building the network, and it is very adept at recognizing the glottis in intubation manikins. Additionally, a novel approach for triggering automatic recording of endotracheal intubation videos is developed, using a facial recognition neural network. Code for the project can be found at https://github.com/c4r5son/britescope and https://github.com/c4r5son/glottisnet.
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2022-04-01
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Undergraduate Honors Theses
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0-Stillman__Carson_cover_sheet.pdf
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Development_of_a_Video_Laryngoscope_with_AI_Assisted_Epiglottis_B.pdf
Adobe PDF, 7.6 MB
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Advisor
Yang, Ran
Cooke, William
Frazier, Rachel
Department
Physics
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https://scholarworks.wm.edu/handle/internal/11301
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