{"paper_id":"31b4f6ba-e67b-423f-a2f7-77c0f426788e","body_text":"Learning From Multiple Readings for Axial Spondyloarthritis Classification of the Sacroiliac Joints | 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 Learning From Multiple Readings for Axial Spondyloarthritis Classification of the Sacroiliac Joints Amir Jamaludin, Rhydian Windsor, Sarim Ather, Gregory Ligozio, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6769491/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Magnetic resonance imaging (MRI) is a cornerstone in the evaluation and monitoring of axial spondyloarthritis (axSpA), a chronic inflammatory condition primarily affecting the sacroiliac joints (SIJs), spine, entheses, and peripheral joints. Accurate quantification of axSpA-related changes in MRI is critical for effective research and patient management. However, current lesion detection and grading assessments suffer from substantial intra- and inter-rater variability, limiting their consistency and reliability. This study addresses these challenges by focusing on automated lesion detection in SIJ MRI to enhance accuracy and reduce variability. Our key contributions include: (i) developing a fully automated pipeline for detecting five distinct MRI lesion types (Bone Marrow Oedema, Ankylosis, Sclerosis, Erosions, Fatty Lesions) in the SIJ, (ii) validating the approach on a completely independent dataset, and (iii) proposing a simple approach to learn a classification model from multiple readings or labels for a given sample. Health sciences/Rheumatology/Rheumatic diseases/Spondyloarthritis Biological sciences/Computational biology and bioinformatics/Image processing Biological sciences/Computational biology and bioinformatics/Machine learning Biological sciences/Computational biology and bioinformatics/Predictive medicine Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 12 Nov, 2025 Reviews received at journal 05 Nov, 2025 Reviewers agreed at journal 24 Oct, 2025 Reviews received at journal 11 Oct, 2025 Reviewers agreed at journal 22 Sep, 2025 Reviewers agreed at journal 02 Sep, 2025 Reviewers invited by journal 28 Jul, 2025 Editor assigned by journal 20 Jul, 2025 Editor invited by journal 10 Jun, 2025 Submission checks completed at journal 07 Jun, 2025 First submitted to journal 07 Jun, 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. 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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-6769491\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":491673657,\"identity\":\"bf000c74-d327-4607-a422-ee2b16d58051\",\"order_by\":0,\"name\":\"Amir 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