Confocal-inspired computational fluorescence microscopy via transfer point spread function

Confocal-inspired computational fluorescence microscopy via transfer point spread function | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Confocal-inspired computational fluorescence microscopy via transfer point spread function Ziwei Wang, Xiaojie Zhang, Jingting Lin, Zimu Zheng, Yupei Miao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9260334/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Laser scanning confocal microscopy provides optical sectioning but is limited by slow acquisition and hardware complexity. Widefield fluorescence microscopy offers high-throughput, low-cost imaging, yet global illumination generates substantial out-of-focus and multiply scattered background. Here we present computational confocal fluorescence microscopy (CCFM), a physics-grounded framework that leverages a transfer point spread functon(TPSF) to reconstruct confocal-like volumes from widefield data. CCFM models widefield imaging as a cascaded process in which scattering-mediated redistribution is followed by system blur, enabling reconstruction beyond standard deconvolution. After a single calibration from paired widefield and confocal volumes, the TPSF can be reused for subsequent widefield imaging under matched imaging conditions and preprocessing strategy, without hardware modification. Across diverse specimens and imaging configurations, CCFM suppresses scattering background and restores optical sectioning beyond standard deconvolution, enabling confocal-like dynamic three-dimensional imaging at widefield speed. Biological sciences/Biological techniques/Imaging/Fluorescence imaging Biological sciences/Biological techniques/Microscopy/Confocal microscopy Biological sciences/Biological techniques/Microscopy/Wide-field fluorescence microscopy Full Text Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryVideo5.mp4 Dynamic imaging of autofluorescent Chlorella by widefield and CCFM. SupplementaryVideo6.mp4 Dynamic imaging of Paramecium during cell lysis by widefield and CCFM. SupplementaryVideo2.mp4 Three-dimensional comparison of butterfly leg imaging by widefield, confocal and CCFM. Supplementary.docx Supplementary Information SupplementaryVideo4.mp4 Three-dimensional comparison of Lilium pollen imaging by widefield, AQ and CCFM. SupplementaryVideo1.mp4 Three-dimensional comparison of rotifer reconstructions by widefield, AQ, confocal and CCFM. SupplementaryVideo3.mp4 hree-dimensional comparison of Cucurbita pollen imaging by widefield, confocal and CCFM. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9260334","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":618634782,"identity":"bd67f4f3-b74b-4cfb-a45e-508306f4ebd2","order_by":0,"name":"Ziwei Wang","email":"","orcid":"","institution":"ShenzhenUniversity","correspondingAuthor":false,"prefix":"","firstName":"Ziwei","middleName":"","lastName":"Wang","suffix":""},{"id":618634783,"identity":"c41554e5-0515-46ca-97f9-efedca07c317","order_by":1,"name":"Xiaojie 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