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. 2019 Jul 12;9:10123. doi: 10.1038/s41598-019-46567-0

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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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Comparison of MMHelper and Molyso performances. Kernel density estimation for precision and recall of channel detection from (A) brightfield and (B) phase contrast images via MMHelper (red) and Molyso³⁰ (blue). The distribution of precision and recall values obtained via MMHelper on phase contrast images tightly clusters around a recall value of 1 and a precision value of 0.55. Therefore, we have zoomed this area in the dashed circle to facilitate its visualisation. (C,D) Corresponding kernel density estimation for precision and recall of bacteria detection. Insets: representative images of channel (A) and bacteria (C) detection.