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. 2019 Jul 15;9:10237. doi: 10.1038/s41598-019-46689-5

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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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Automated cell boundary segmentation. (A) Workflow of the automated cell boundary segmentation. (B–G) Images showing individual processing steps: (B) Maximum projected widefield image using several images with clear cell boundaries is used to generate a (C) background image using disk smoothing. (D) After background subtraction, the maximum projected widefield image is overlaid with the segmented nuclei. (E) A watershed algorithm is applied resulting in segmented cells with cells on the image boundary removed (F). (G) Overlay of widefield (grey), DAPI (blue), nuclear (yellow) and cytoplasmic (magenta) segmented mESC. Scalebar 13.3 µm (H) Cell segmentation accuracy (F1-score) quantification of 2D cell segmentation comparing fully automated adaptive threshold algorithm CellDissect (blue), maximum nuclei threshold algorithm (orange) and manual thresholding (yellow) in comparison to manual segmentation in four different cell lines and two different imaging magnifications. Mean and standard deviations are computed from quantifying the 3–4 images by three independent human experts (left) or 3 replicas by one human expert (right).