Enhancing brain image segmentation: A metaheuristic approach to multi-threshold optimization

Enhancing brain image segmentation: A metaheuristic approach to multi-threshold optimization | 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 Enhancing brain image segmentation: A metaheuristic approach to multi-threshold optimization Fernando Ramirez, Emilio Flores, Rodrigo Olivares This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5320602/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 Brain segmentation is vital for the accurate diagnosis and treatment of neurological disorders, given the complexity and vulnerability of the brain to various pathologies such as strokes and tumors. The challenge lies in achieving precise delineation of anatomical and pathological structures within medical images, particularly under varying conditions of image quality and tissue irregularities. To address this, we applied eight metaheuristic optimization algorithms-Reptile Search Algorithm, Orca Predator Algorithm, Bald Eagle Search, Grey Wolf Optimizer, Honey Badger Algorithm, Crow Search Algorithm, Harris Hawk Optimization, and Tuna Swarm Optimization-to improve the accuracy of multi-threshold segmentation methods like Kapur’s entropy, Tsallis entropy, and the Otsu method. The results reveal that the Grey Wolf Optimizer and Tuna Swarm Optimization stand out, with the Grey Wolf Optimizer demonstrating superior performance across key metrics such as Peak Signal to Noise Ratio and Structural Similarity Index. These outcomes highlight the potential of the Grey Wolf Optimizer for advanced brain tissue segmentation, offering significant advantages in clinical and research environments where precision is essential for effective medical intervention. Nature-inspired optimization algorithm Kapur’s Entropy Tsallis Entropy Otsu Method Medical Image Segmentation Full Text Additional Declarations No competing interests reported. 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-5320602","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":369978640,"identity":"e901d22c-253d-43a6-8de8-331370092b88","order_by":0,"name":"Fernando Ramirez","email":"","orcid":"","institution":"University of Valparaíso","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"","lastName":"Ramirez","suffix":""},{"id":369978641,"identity":"5fe8b396-ea4d-4f66-8957-b9eb837dd361","order_by":1,"name":"Emilio Flores","email":"","orcid":"","institution":"University of Valparaíso","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Emilio","middleName":"","lastName":"Flores","suffix":""},{"id":369978642,"identity":"d56154c9-06c5-4d31-a748-ccbdad43b99f","order_by":2,"name":"Rodrigo Olivares","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYHACA4YEEMXO2ADm8oPJAmK0MEO1SDZABPFrAQNmGPcAAS3m7c3bPjz4ZcPAz8zcJvFzj4298Y0cA4YfeLTInDlWPCOxL41BspmxTbLnWVriNqAWxh48WiQkcowZEnsOMxgcZmw24DlwOMHsRloCMz6HoWgx/HPgv73xDGK0JPwAa2l8zHPgAOMGieQD+LXwHCtmSGxI4wH6pfGxzIHkxBlnHh84iNcv7M2bGX/8sZHjZ29/cPDNATt7/vbExgc/KnBrAQPGNgYeFIEDBDQAwR/CSkbBKBgFo2AEAwCqLkzGKawDlwAAAABJRU5ErkJggg==","orcid":"","institution":"University of Valparaíso","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rodrigo","middleName":"","lastName":"Olivares","suffix":""}],"badges":[],"createdAt":"2024-10-23 16:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5320602/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5320602/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69481778,"identity":"428affea-429e-4be9-aaf1-451efef8dff1","added_by":"auto","created_at":"2024-11-20 22:16:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2367328,"visible":true,"origin":"","legend":"","description":"","filename":"SpringerNatureLaTeXTemplate.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5320602/v1_covered_4d23e6fe-d170-4a89-b9a8-5149da96a1e0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhancing brain image segmentation: A metaheuristic approach to multi-threshold optimization","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":"Nature-inspired optimization algorithm, Kapur’s Entropy, Tsallis Entropy, Otsu Method, Medical Image Segmentation","lastPublishedDoi":"10.21203/rs.3.rs-5320602/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5320602/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Brain segmentation is vital for the accurate diagnosis and treatment of neurological disorders, given the complexity and vulnerability of the brain to various pathologies such as strokes and tumors. 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