Performance of machine learning algorithms for glioma segmentation of brain MRI: a systematic literature review and meta-analysis.

Evi J van KempenMax PostManoj MannilRichard L WitkamMark Ter LaanAjay PatelFrederick J A MeijerDylan Jozef Hendrik Augustinus Henssen

Published in: European radiology (2021)

• MLAs from the included studies showed an overall DSC score of 0.84 (95% CI: 0.82-0.86), indicating a good performance. • MLA performance was comparable when comparing the segmentation results of the high-grade gliomas and the low-grade gliomas. • For future studies using MLAs, it is crucial that quality guidelines are followed when reporting on MLAs, which includes validation on an external test set.

Keyphrases

high grade
low grade
machine learning
deep learning
convolutional neural network
case control
artificial intelligence
magnetic resonance imaging
white matter
big data
resting state
clinical practice
current status
computed tomography
adverse drug
quality improvement
magnetic resonance