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. 2022 Jan 20;15:805669. doi: 10.3389/fninf.2021.805669

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Copyright © 2022 Bento, Fantini, Park, Rittner and Frayne.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Example of fluid-attenuated inversion recovery (FLAIR) images in a multi-site dataset: (A) healthy control participant imaged on a specific scanner vendor; (B) a patient with a pathology (white matter hyperintensities, WMH, Wardlaw et al., 2013) imaged on the same scanner vendor; (C) a second patient with WMH pathology imaged on a different scanner vendor. Images acquired using different scanner vendors may present different image contrasts, shape, and other characteristics. These varying characteristics may impact the DL models development and performance due to unwanted correlations in the dataset (that are not correlated with the pathology occurrence).