<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Aidukas T</submitter><funding>RCUK | Engineering and Physical Sciences Research Council</funding><funding>Engineering and Physical Sciences Research Council</funding><pagination>7457</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6520337</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>9(1)</volume><pubmed_abstract>The revolution in low-cost consumer photography and computation provides fertile opportunity for a disruptive reduction in the cost of biomedical imaging. Conventional approaches to low-cost microscopy are fundamentally restricted, however, to modest field of view (FOV) and/or resolution. We report a low-cost microscopy technique, implemented with a Raspberry Pi single-board computer and color camera combined with Fourier ptychography (FP), to computationally construct 25-megapixel images with sub-micron resolution. New image-construction techniques were developed to enable the use of the low-cost Bayer color sensor, to compensate for the highly aberrated re-used camera lens and to compensate for misalignments associated with the 3D-printed microscope structure. This high ratio of performance to cost is of particular interest to high-throughput microscopy applications, ranging from drug discovery and digital pathology to health screening in low-income countries. 3D models and assembly instructions of our microscope are made available for open source use.</pubmed_abstract><journal>Scientific reports</journal><pubmed_title>Low-cost, sub-micron resolution, wide-field computational microscopy using opensource hardware.</pubmed_title><pmcid>PMC6520337</pmcid><funding_grant_id>1807419</funding_grant_id><funding_grant_id>EP/L016753/1</funding_grant_id><pubmed_authors>Konda PC</pubmed_authors><pubmed_authors>Eckert R</pubmed_authors><pubmed_authors>Harvey AR</pubmed_authors><pubmed_authors>Aidukas T</pubmed_authors><pubmed_authors>Waller L</pubmed_authors></additional><is_claimable>false</is_claimable><name>Low-cost, sub-micron resolution, wide-field computational microscopy using opensource hardware.</name><description>The revolution in low-cost consumer photography and computation provides fertile opportunity for a disruptive reduction in the cost of biomedical imaging. Conventional approaches to low-cost microscopy are fundamentally restricted, however, to modest field of view (FOV) and/or resolution. We report a low-cost microscopy technique, implemented with a Raspberry Pi single-board computer and color camera combined with Fourier ptychography (FP), to computationally construct 25-megapixel images with sub-micron resolution. New image-construction techniques were developed to enable the use of the low-cost Bayer color sensor, to compensate for the highly aberrated re-used camera lens and to compensate for misalignments associated with the 3D-printed microscope structure. This high ratio of performance to cost is of particular interest to high-throughput microscopy applications, ranging from drug discovery and digital pathology to health screening in low-income countries. 3D models and assembly instructions of our microscope are made available for open source use.</description><dates><release>2019-01-01T00:00:00Z</release><publication>2019 May</publication><modification>2026-05-06T21:53:20.27Z</modification><creation>2019-06-06T23:15:53Z</creation></dates><accession>S-EPMC6520337</accession><cross_references><pubmed>31092867</pubmed><doi>10.1038/s41598-019-43845-9</doi></cross_references></HashMap>