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. 2019 Dec 30;9:20311. doi: 10.1038/s41598-019-56767-3

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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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Feature extraction by AlexNet. The lesion image was cut out using a VOI and resized to 243 × 243 pixels. The image was cropped to 227 × 227 pixels with a shift of ±8 pixels and rotated/flipped for data augmentation. The augmented image was input to the pretrained AlexNet to acquire the texture features for classification.