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. 2019 Jun 4;13:42. doi: 10.3389/fninf.2019.00042

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Copyright © 2019 Pallast, Diedenhofen, Blaschke, Wieters, Wiedermann, Hoehn, Fink and Aswendt.

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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Quantitative registration quality control using a slice-wise comparison of N_T = 40 imaging data grouped in four sets with three metrics [L2-Norm, Structural Similarity Index (SSIM), Cross-Correlation (CrC)] between AIDAmri I_A and two observers I₀₁ and I₀₂. The different properties of each data sets are listed in Table 2 and one example slice is shown above each evaluation. Whereas, the ground-truth was determined with the error range of I₀₁/I₀₂, the average error between the automated approach of AIDAmri and the observer-dependent approach I_A/I₀₁ and I_A/I₀₂ showed no significant differences in all three metrices.