Leonardo: A Toolset to Remove Sample-Induced Aberrations in Light Sheet Microscopy Images

Leonardo: A Toolset to Remove Sample-Induced Aberrations in Light Sheet Microscopy Images | 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 Leonardo: A Toolset to Remove Sample-Induced Aberrations in Light Sheet Microscopy Images Tingying Peng, Yu Liu, Gesine Müller, Lennart Kowitz, Tomas Chobola, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5853941/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Selective plane illumination microscopy (SPIM, also known as light sheet fluorescence microscopy) is the method of choice for studying organ morphogenesis and function, as it permits gentle and rapid volumetric imaging of biological specimens over days. In inhomogeneous samples, however, sample-induced aberrations, including light absorption, scattering, and refraction, can degrade the image, particularly as the focal plane gets deeper into the sample. Here, we present Leonardo, the first toolbox capable of resolving all sample-induced aberrations by using two modules: (1) DeStripe removes stripe artifacts in SPIM caused by light absorption; (2) Fuse reconstructs a single high-quality image from dual-sided illumination and/or dual-sided detection, while eliminating blur and optical distortions caused by light scattering and refraction. The efficacy of Leonardo is validated on a wide range of biological systems, from minimally invasive experiments on sensitive specimens (relatively translucent embryonic and optically opaque larval zebrafish) to immunolabeled mice up to 2 centimeters in size. We provide model code and a Napari-based graphical user interface, enabling the SPIM community to easily apply Leonardo to advance light sheet imaging of inhomogeneous and complex specimens. Biological sciences/Biological techniques/Microscopy/Light-sheet microscopy Biological sciences/Biological techniques/Software selective plane illumination microscopy (SPIM) light sheet fluorescence microscopy (LSFM) artificial intelligence (AI) machine learning (ML) sample-induced aberrations image processing research software Full Text Additional Declarations There is NO Competing Interest. Supplementary Files extendeddatafigures.pdf supplementaryinformation.pdf supplementaryvideo1.mp4 Demo of Leonardo-DeStripe on a fixed murine heart tissue supplementaryvideo2.mp4 Demo of Leonardo-DeStripe on zebrafish brain tissue supplementaryvideo3.mp4 Demo of Leonardo-Fuse on zebrafish larva supplementaryvideo4.mp4 Demo of Leonardo-Fuse on a live 2-days-post-fertilization (2dpf) transgenic zebrafish supplementaryvideo5.mp4 Demo of Leonardo-Fuse on zebrafish Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version 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-5853941","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":405818427,"identity":"07be0917-dc91-485f-8428-6c5daaf99c0f","order_by":0,"name":"Tingying 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