A novel Vmamba-based deep learning model for accurate nuclei and cytoplasm segmentation in cervical cytology images

A novel Vmamba-based deep learning model for accurate nuclei and cytoplasm segmentation in cervical cytology 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 Research Article A novel Vmamba-based deep learning model for accurate nuclei and cytoplasm segmentation in cervical cytology images Baocan Zhang, Peng Lin, Wei Zhao, Xiaolu Jiang, Xingbei Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7672152/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Cervical cancer continues to be a major global health challenge, and robust screening capabilities remain the most effective strategy for its prevention. Within this context, image segmentation plays a critical role in screening processes,as it enables a more precise analysis of cellular morphological features, therebyimproving diagnostic accuracy. This paper presents a method for three-class cellsegmentation into nucleus, cytoplasm and background, by combining the backbonenetwork Vmamba and transformer-based segmentation head. The model is fine-tunedon the Herlev dataset and outperforms state-of-the-art methods by moderate margin.Across the tasks of nucleus and cytoplasm segmentation, the model yields average scores of 0.9372 for Dice, 0.8819 for IoU, 0.9217 for Precision, and 0.9551 for Recall.These results demonstrate the suitability of the proposed segmentation model to help experts effectively asset cervical cell lesions. Vmamba Mask2Former semantic segmentation cervical cytology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 28 Sep, 2025 Reviewers invited by journal 27 Sep, 2025 Editor assigned by journal 22 Sep, 2025 Submission checks completed at journal 22 Sep, 2025 First submitted to journal 22 Sep, 2025 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7672152","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":526181623,"identity":"71ffc0cc-816c-42b8-8c5f-61a4763fa936","order_by":0,"name":"Baocan Zhang","email":"","orcid":"","institution":"Chengyi College, Jimei University","correspondingAuthor":false,"prefix":"","firstName":"Baocan","middleName":"","lastName":"Zhang","suffix":""},{"id":526181624,"identity":"9df8ea04-54a4-4e50-8ed7-81911309fbe9","order_by":1,"name":"Peng Lin","email":"","orcid":"","institution":"Chengyi College, Jimei 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