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. 2019 Jul 4;9:9649. doi: 10.1038/s41598-019-46030-0

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© The Author(s) 2019

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Overview of robustness analysis to linear interpolation for 78 texture features. Left. ICC(2,1) with 95% confidence intervals for each feature. ICC highlighted in green (>0.9), yellow (0.75–0.9), orange (0.5–0.75) and red (<0.5). Right. Pairwise patient ranking correlation between the 2.7 mm rankings and all other voxel sizes for each feature. ρ_mean > 0.95 is highlighted with a closed dot. Features were categorised as R (Robust), LR, (limited Robustness), C (Potentially Correctable) and NR (Not Robust) based on criteria outlined in Fig. 1.