Validation and comparison of two automated methods for quantifying brain white matter hyperintensities of presumed vascular origin.

Jennifer M J Waymont Chariklia PetsaChris J McNeilAlison D MurrayGordon D Waiter

Published in: The Journal of international medical research (2019)

LGA appeared to be the most suitable algorithm for quantifying WMH in relation to cerebral small vessel disease, compared with Scheltens' score and manual segmentation. LGA offers a user-friendly, effective WMH segmentation method in the research environment.

Keyphrases

deep learning
white matter
convolutional neural network
multiple sclerosis
machine learning
subarachnoid hemorrhage
cerebral ischemia
brain injury
high throughput
blood brain barrier