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. 2021 Nov 25;11:22920. doi: 10.1038/s41598-021-01929-5

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© The Author(s) 2021

Open AccessThis 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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Threshold optimization. On the left, the $F_{1}$ score computed on validation images as a function of the cutoff for thresholding. On the right, the test $F_{1}$ score of the c-ResUnet model is used to illustrate the selection of the best threshold for binarization according to argmax (blue) and kneedle (red) methods.