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. 2020 Feb 7;11:771. doi: 10.1038/s41467-020-14529-0

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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 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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Fig. 6 — A 3D ROI from a FIB-SEM data set, acquired at isotropic 5-nm resolution, from mouse heart tissue was used for denoising. a An XY view of 330 × 300 pixels of the raw image. b The image was used for creating a mask (in green) by intensity thresholding. c This mask was used for 3D rendering with the ImageJ 3D Viewer. d The data were denoised with DenoisEM, using the NLM algorithm, and e, f segmented by thresholding. g The ROI indicated in panel (a) was used for manual counting of sarcomeres with the ImageJ Cell Counter Plugin. h Each item counted is indicated with a magenta dot. Panels (i) and (j) show the counting results on the denoised data. k A graph showing the number of sarcomeres counted, either manual by three different individuals or by the ImageJ Analyse Particles tool on a thresholded image, with or without watershed.