Automated Montaging of Ultrasound Scans for Determination of Ocular Globe Shape

Automated Montaging of Ultrasound Scans for Determination of Ocular Globe Shape | 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 Automated Montaging of Ultrasound Scans for Determination of Ocular Globe Shape Yue Zhang, Marielle Reidy, Swati Padhee, Nathan Doble, Donald Mutti, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8835197/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Introduction: The global increase in myopia highlights the urgent need for reliable and automated methods to monitor structural changes in the eye, especially in the peripheral regions beyond the central fovea, where conventional imaging is limited. This study develops and validates an automated pipeline that enables comprehensive assessment of posterior eye shape from extended-range B-scan ultrasonography, addressing the limitations of current partial coherence interferometry and manual alignment approaches.Methods: Extended-range B-scan ultrasound images were acquired at three gaze angles to capture peripheral retinal dimensions. The method utilizes the Segment Anything Model (SAM) for interactive and accurate boundary segmentation, followed by translation-based alignment to merge the triplet of images into a unified posterior eye wall representation. Multi-set averaging across repeated acquisitions was further evaluated for enhancing reproducibility. SAM results were compared to those from manual merging of images. Results: Averaging multiple frames before merging significantly reduced the standard deviation of measurements and improved consistency compared with merging a single image. Using this automated triplet-merging approach, reproducibility yielded mean absolute improvements of 31.46 microns (30.12%) in the horizontal view and 29.04 microns (39.53%) in the vertical view relative to manual merging, indicating greater reproducibility and stability across acquisitions.Conclusion:The proposed operator-independent pipeline provides a scalable, consistent assessment of peripheral eye morphology. By enabling automated quantification of retinal curvature and globe shape, this approach supports more precise monitoring of myopia progression and enhances the reliability of evaluating treatment efficacy in both clinical trials and routine practice. myopia globe shape ultrasound artificial intelligence retinal curvature Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 17 May, 2026 Reviewers agreed at journal 13 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers invited by journal 23 Feb, 2026 Editor assigned by journal 11 Feb, 2026 Submission checks completed at journal 11 Feb, 2026 First submitted to journal 09 Feb, 2026 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-8835197","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595547948,"identity":"d1668f46-c200-42a6-bbdc-bf2684ad64fd","order_by":0,"name":"Yue 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This study develops and validates an automated pipeline that enables comprehensive assessment of posterior eye shape from extended-range B-scan ultrasonography, addressing the limitations of current partial coherence interferometry and manual alignment approaches.Methods: Extended-range B-scan ultrasound images were acquired at three gaze angles to capture peripheral retinal dimensions. The method utilizes the Segment Anything Model (SAM) for interactive and accurate boundary segmentation, followed by translation-based alignment to merge the triplet of images into a unified posterior eye wall representation. Multi-set averaging across repeated acquisitions was further evaluated for enhancing reproducibility. SAM results were compared to those from manual merging of images. Results: Averaging multiple frames before merging significantly reduced the standard deviation of measurements and improved consistency compared with merging a single image. Using this automated triplet-merging approach, reproducibility yielded mean absolute improvements of 31.46 microns (30.12%) in the horizontal view and 29.04 microns (39.53%) in the vertical view relative to manual merging, indicating greater reproducibility and stability across acquisitions.Conclusion:The proposed operator-independent pipeline provides a scalable, consistent assessment of peripheral eye morphology. By enabling automated quantification of retinal curvature and globe shape, this approach supports more precise monitoring of myopia progression and enhances the reliability of evaluating treatment efficacy in both clinical trials and routine practice.\u003c/p\u003e","manuscriptTitle":"Automated Montaging of Ultrasound Scans for Determination of Ocular Globe Shape","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-25 11:22:50","doi":"10.21203/rs.3.rs-8835197/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-17T16:47:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"302153203447932088348255660492514803143","date":"2026-05-14T03:20:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"67890700839609019814373996725127687028","date":"2026-05-12T22:09:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196619258467860057188859190285953054590","date":"2026-05-12T07:20:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"221423785100582571770254965384560480011","date":"2026-03-03T00:46:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-23T10:03:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-11T16:30:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-11T11:39:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Ophthalmic and Physiological Optics","date":"2026-02-10T01:33:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"ophthalmic-and-physiological-optics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Ophthalmic and Physiological Optics](https://link.springer.com/journal/44402)","snPcode":"44402","submissionUrl":"https://submission.springernature.com/new-submission/44402/3?","title":"Ophthalmic and Physiological Optics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5de3750f-01ad-4a71-b2eb-b4955e87b7cc","owner":[],"postedDate":"February 25th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-17T16:47:01+00:00","index":24,"fulltext":""},{"type":"reviewerAgreed","content":"302153203447932088348255660492514803143","date":"2026-05-14T03:20:10+00:00","index":23,"fulltext":""},{"type":"reviewerAgreed","content":"67890700839609019814373996725127687028","date":"2026-05-12T22:09:06+00:00","index":22,"fulltext":""},{"type":"reviewerAgreed","content":"196619258467860057188859190285953054590","date":"2026-05-12T07:20:54+00:00","index":21,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-25T11:22:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-25 11:22:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8835197","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8835197","identity":"rs-8835197","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}