Evaluation of automated tool for two-dimensional fetal biometry.

Ibtisam Salim Angelo CavallaroC Ciofolo-VeitL RouetC RaynaudB MoryA Collet BillonG HarrisonD RoundhillAris T Papageorghiou

Published in: Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology (2019)

The automated tool identified correctly the biometric variable of interest in 99% of frozen images. The resulting measurements had a high degree of accuracy and compared well with previously published manual-to-manual agreement. The measurements exhibited bias, with the automated tool underestimating biometry; this could be overcome by further improvements in the algorithm. Nevertheless, adjustable calipers for manual correction remains a requirement. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

Keyphrases

deep learning
machine learning
high throughput
convolutional neural network
randomized controlled trial