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. 2020 Aug 4;19(2):267–284. doi: 10.1007/s12021-020-09483-7

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© The Author(s) 2020

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. 8 — The performance and quantitative assessment of SyN and DeepMapi on the LONI LPBA40 datasets. a The registration results of SyN (ground truth) and DeepMapi. Three standard anatomical planes are presented from left to right and the four columns correspond to the moving image, fixed image, SyN registration results and DeepMapi registration results, respectively. The brown boxes represents the same spatial position for the comparisons. b Quantitative assessment of 56 brain regions. The Dice scores of nine brain datasets are presented in a box plot. Brown: DeepMapi. Black: SyN. The regions where DeepMapi achieved a higher median value than SyN are marked with an asterisk (*)