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. 2023 Oct 11;46(4):1791–1802. doi: 10.1007/s13246-023-01342-4

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — Boxplots of the evaluation metrics used in this study for comparisons between the semi-automated rigid-, automated rigid and non-rigid registration algorithm performance. (a) DSI values. (b) 95% HD values. (c) ASD values. The boxplot centreline marks the median value. DSI, dice similarity index; HD, Hausdorff distance; ASD, average surface distance; Auto, automated; ***, p < 0.001