Structural and Statistical Texture Approaches in the Radiological Assessment of Knee Osteoarthritis: A Multimodal Review

Structural and Statistical Texture Approaches in the Radiological Assessment of Knee Osteoarthritis: A Multimodal Review | 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 Structural and Statistical Texture Approaches in the Radiological Assessment of Knee Osteoarthritis: A Multimodal Review Sujeet More, Geetika Narang, Amol Bhosale, Rupali Maske This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7239085/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 Knee osteoarthritis (KOA) represents a significant degenerative joint disorder characterized by the progressive deterioration of articular cartilage. The therapeutic approach to KOA is contingent upon disease progression. Contemporary diagnostic methodologies encompass both traditional clinical assessments and automated diagnostic systems. Digital imaging-based diagnostic platforms facilitate early detection of KOA manifestations. Recent technological advancements have yielded sophisticated analytical methods, including Histogram of Oriented Gradients (HOG), fractal analysis, and Local Binary Patterns (LBP), which have emerged as valuable diagnostic tools over the past decade. This comprehensive review examines the diverse array of texture analysis methodologies employed in KOA detection across multiple imaging modalities, including Computed Tomography (CT), X-ray radiography, and Magnetic Resonance Imaging (MRI). The primary objectives of this investigation are multifaceted; To introduce novel methodological approaches in the field; To systematically categorize significant contributions in image-based texture analysis; To delineate principal challenges and significant findings; To evaluate existing research protocols and diagnostic questionnaires, and to propose strategic recommendations for enhancing diagnostic precision in KOA assessment. The analytical framework encompasses statistical, structural, transform-based, and model-based methodologies. This review synthesizes findings from more than 60 peer-reviewed publications, categorized according to their methodological approach, imaging modality, and classification algorithms. Each methodological section presents a detailed analysis of the respective approaches, including their theoretical foundations, practical applications, and inherent limitations. Knee osteoarthritis X-ray CT Scan MRI Texture analysis Classification 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. 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-7239085","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492378050,"identity":"8c5f2a3e-9cdf-40fe-b76e-50403291bd79","order_by":0,"name":"Sujeet More","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYHCCBCjN//EBkOThI04LRJexAUgLGykWmUmASIJa5GckPHzw8cc2OfP2hrTKrzl2MmwMzA8f3cCjxeBGQrLhjITbxjJnDhy7LbstGegwNmPjHHxaJBLSpHkSbifOkEhsuy25jRmohYdNGp8WoMPSf/8BaZF/zFYsua2esBaGGwlpzAxgW9jYGD9uO0xYi8GZB8mSPWm3jSV4cpilGbcd52FjJuAX+facxA8/bG7LSbCfYfz4c1u1PT9788PHeB3GwJMAZzLzgEm8ykGA/QCcyfiDoOpRMApGwSgYiQAAY8tF+kvvJTwAAAAASUVORK5CYII=","orcid":"","institution":"Trinity College of Engineering and Research","correspondingAuthor":true,"prefix":"","firstName":"Sujeet","middleName":"","lastName":"More","suffix":""},{"id":492378053,"identity":"1f490443-08d2-4d21-8e4a-b80e496230ab","order_by":1,"name":"Geetika Narang","email":"","orcid":"","institution":"Trinity College of Engineering and Research","correspondingAuthor":false,"prefix":"","firstName":"Geetika","middleName":"","lastName":"Narang","suffix":""},{"id":492378055,"identity":"c253f19b-07d6-486e-9b52-7ea738562659","order_by":2,"name":"Amol Bhosale","email":"","orcid":"","institution":"Trinity College of Engineering and Research","correspondingAuthor":false,"prefix":"","firstName":"Amol","middleName":"","lastName":"Bhosale","suffix":""},{"id":492378057,"identity":"510f689f-72ee-456b-a37f-19f09b8252cc","order_by":3,"name":"Rupali Maske","email":"","orcid":"","institution":"Trinity College of Engineering and Research","correspondingAuthor":false,"prefix":"","firstName":"Rupali","middleName":"","lastName":"Maske","suffix":""}],"badges":[],"createdAt":"2025-07-29 05:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7239085/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7239085/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89344450,"identity":"e5940f00-a7a2-46fc-b123-6447ee319ea3","added_by":"auto","created_at":"2025-08-19 04:16:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":977445,"visible":true,"origin":"","legend":"","description":"","filename":"ReviewPaperOsteoarthritis.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7239085/v1_covered_dcce38ec-7cfd-4731-843a-cc7cdcf155d8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Structural and Statistical Texture Approaches in the Radiological Assessment of Knee Osteoarthritis: A Multimodal Review","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Knee osteoarthritis, X-ray, CT Scan, MRI, Texture analysis, Classification","lastPublishedDoi":"10.21203/rs.3.rs-7239085/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7239085/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eKnee osteoarthritis (KOA) represents a significant degenerative joint disorder characterized by the progressive deterioration of articular cartilage. The therapeutic approach to KOA is contingent upon disease progression. Contemporary diagnostic methodologies encompass both traditional clinical assessments and automated diagnostic systems. Digital imaging-based diagnostic platforms facilitate early detection of KOA manifestations. Recent technological advancements have yielded sophisticated analytical methods, including Histogram of Oriented Gradients (HOG), fractal analysis, and Local Binary Patterns (LBP), which have emerged as valuable diagnostic tools over the past decade. This comprehensive review examines the diverse array of texture analysis methodologies employed in KOA detection across multiple imaging modalities, including Computed Tomography (CT), X-ray radiography, and Magnetic Resonance Imaging (MRI). 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