Rank-based Transformation for Image Contrast Adjustment Enhances Cell Segmentation

Rank-based Transformation for Image Contrast Adjustment Enhances Cell Segmentation | 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 Rank-based Transformation for Image Contrast Adjustment Enhances Cell Segmentation Cheng-Hui Chen, Torbjörn Nordling This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6886043/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 Proper image contrast adjustment without information loss is essential but challenging, often requiring experience or trial and error. Nonetheless, we expected that the multiple normalization steps embedded in deep neural networks would render external contrast adjustment redundant in modern cell segmentation tools--but that is not the case. We evaluate the impact of contrast preprocessing on three state-of-the-art segmentation tools: Cellpose, PlantSeg, and Ilastik. Contrast adjustment via the rank-based transformation (RBT) method requires no parameter tuning or prior knowledge. RBT computes pixel ranks and maps them across the full dynamic range, ensuring uniform contrast enhancement without information loss. It is particularly effective for underexposed images. Preprocessing with RBT leads to visibly improved segmentation in advanced tools like Cellpose. Our results falsify the claim that modern segmentation tools are insensitive to contrast preprocessing. Physical sciences/Mathematics and computing/Computer science Biological sciences/Microbiology Biological sciences/Computational biology and bioinformatics/Image processing Biological sciences/Computational biology and bioinformatics/Machine learning Biological sciences/Cell biology/Cellular imaging Full Text Additional Declarations No competing interests reported. Supplementary Files RBTScientificReportsSuppl.pdf 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-6886043","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":484015213,"identity":"438dc670-32cc-4a75-9603-8611bd034544","order_by":0,"name":"Cheng-Hui Chen","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Cheng-Hui","middleName":"","lastName":"Chen","suffix":""},{"id":484015214,"identity":"21a9e81f-f7f0-4749-9ff2-633b7086efe5","order_by":1,"name":"Torbjörn Nordling","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYDAC9gYgwWbBw8DA3MBMlA4engMgLRJALYzEapFIAGthIF6LveTbg48ryiRkzPkXNn4uYLDJl3cgZIt0XrLhmXMSPJYzHjZLz2BIs9x4gKCWHDPJxjYJHoMbBxukeRgOGxg2ENIieQaupfk3cVokeKBazje2gW2RJ6CDgedMjrFhwzmQLYxt1jMM0gwMCGlhbz9j+LChzMbe4Pzhw7cLKmwM5Ak5DAHAEQS0wuAA0Vr4oUpJsGUUjIJRMApGCAAA5kw410p8MksAAAAASUVORK5CYII=","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":true,"prefix":"","firstName":"Torbjörn","middleName":"","lastName":"Nordling","suffix":""}],"badges":[],"createdAt":"2025-06-13 08:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6886043/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6886043/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89508398,"identity":"a0436e33-91a8-4128-9621-71ff6c0382f7","added_by":"auto","created_at":"2025-08-20 17:46:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":837155,"visible":true,"origin":"","legend":"","description":"","filename":"RBTScientificReport.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6886043/v1_covered_0b14d091-96df-42c6-bde8-b60e8d7f73aa.pdf"},{"id":86746474,"identity":"213f8864-18e6-43d2-bf28-2389d0a45319","added_by":"auto","created_at":"2025-07-15 07:49:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1276831,"visible":true,"origin":"","legend":"","description":"","filename":"RBTScientificReportsSuppl.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6886043/v1/1258184c675ae49ce87fe74a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rank-based Transformation for Image Contrast Adjustment Enhances Cell Segmentation","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6886043/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6886043/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Proper image contrast adjustment without information loss is essential but challenging, often requiring experience or trial and error. 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