Validation of a Denoising Method Using Deep Learning-Based Reconstruction to Quantify Multiple Sclerosis Lesion Load on Fast FLAIR Imaging.

Takayuki Yamamoto C Lacheret Hikaru Fukutomi R A Kamraoui L Denat Bei Zhang V H Prevost L Zhang Aurélie Ruet B Triaire Vincent Dousset Pierrick Coupé Thomas Tourdias

Published in: AJNR. American journal of neuroradiology (2022)

Denoising using deep learning-based reconstruction helps to recognize multiple sclerosis lesions buried in the noise of accelerated FLAIR acquisitions, a possibly useful strategy to efficiently shorten the scan time in clinical practice.

Keyphrases

multiple sclerosis
deep learning
convolutional neural network
clinical practice
artificial intelligence
white matter
high resolution
machine learning
computed tomography
air pollution