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. 2019 Sep 19;9:13597. doi: 10.1038/s41598-019-49506-1

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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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Visualisation of the mean shape and variation for a non-patient face, a preoperative face, and a postoperative face. A qualitative illustration of the mean shape (μ) and first five shape eigenvectors, with weights for the standard deviation (σ_i) of + 3σ_i (top row) and −3σ_i (bottom row). (a) LSFM represented a non-patient population and acted as a benchmark for our models. (b) The bespoke preoperative model, constructed from preoperative 3D scans (n = 119). (c) The bespoke postoperative model, constructed from postoperative 3D scans (n = 127).