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. 2019 Mar 8;9:3926. doi: 10.1038/s41598-019-40554-1

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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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Visualized result for the pixel size-limited system. Deep learning-based pixel super-resolution imaging of a Pap smear slide under 550 nm illumination. (a) Whole FOV of the lensfree imaging system. (b) Amplitude and phase channels of the network output. (c) Further zoom-in of (b) for two regions of interest. The marked region in the first column demonstrates the network’s ability to process the artifacts caused by out-of-focus particles within the sample.