Unsupervised Learning-Based Measurement of Ultrasonic Axial Transmission Velocity in Neonatal Bone.

Qing LiLawrence H LeJialin GuoBoyi LiKailiang XuLawrence H LeDean Ta

Published in: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine (2024)

These findings suggest that fuzzy C-means clustering is highly effective in extracting ultrasonic propagating velocity in bone and reliably applicable in in vivo measurement. This work is a preliminary study that holds promise in advancing the development of a standardized ultrasonic tool for assessing neonatal bone health. Such advancements are crucial in the accurate diagnosis of bone growth disorders.

Keyphrases

bone mineral density
soft tissue
bone loss
bone regeneration
machine learning
mental health
body composition
blood flow
risk assessment
climate change
deep learning
neural network
health promotion