A Deep Learning Framework for Analysis of the Eustachian Tube and the Internal Carotid Artery.

Ameen Amanian Aseem JainYuliang XiaoChanha KimAndy S DingManish SahuRussell TaylorMathias UnberathBryan K WardDeepa GalaiyaMasaru IshiiFrancis X Creighton

Published in: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery (2024)

This study describes the first end-to-end DL pipeline for automated ET and ICA segmentation and analyzes distances between these structures. In addition to helping to ensure the safe selection of patients for ET dilation, this method can facilitate large-scale studies exploring the relationship between ET pathologies and the 3D shape of the ET.

Keyphrases

deep learning
internal carotid artery
end stage renal disease
convolutional neural network
ejection fraction
machine learning
newly diagnosed
artificial intelligence
middle cerebral artery
prognostic factors
high throughput
high resolution
patient reported