Automated semantic labeling of pediatric musculoskeletal radiographs using deep learning.

Paul H YiTae Kyung KimJinchi WeiJiwon ShinFerdinand K HuiHaris I SairGregory D HagerJan Fritz

Published in: Pediatric radiology (2019)

DCNNs trained on a small set of images with 30 times augmentation through standard processing techniques are able to automatically classify pediatric musculoskeletal radiographs into anatomical region with near-perfect to perfect accuracy at superhuman speeds. This concept may apply to other body parts and radiographic views with the potential to create an all-encompassing semantic-labeling DCNN.

Keyphrases

deep learning
convolutional neural network
artificial intelligence
machine learning
high throughput
optical coherence tomography
risk assessment
soft tissue
high intensity
body composition