Computer-aided Segmentation of Foveal Avascular Zone in OCT-A Images

Computer-aided Segmentation of Foveal Avascular Zone in OCT-A 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 Computer-aided Segmentation of Foveal Avascular Zone in OCT-A Images Arpan Chandra, Poulomi Mukherjee, Debolina Banerjee, Anupama Mukherjee, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7315531/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 Precise segmentation of the foveal avascular zone (FAZ) is critical because FAZ size and integrity are significant predictors of retinal health and visual acuity. FAZ area measurement holds substantial research value, as it provides additional information that can be used to develop new treatment modalities. Quantitative evaluation of the FAZ can detect early retinal microvascular alterations that are not yet symptomatic. In this paper, a computationally light deep neural network structure is built for the segmentation of FAZ in OCT-A images. The model should be computationally light and have high accuracy, thus being appropriately applied in clinical scenarios and deployed in environments with limited resources. Our structure outperforms traditional structures in both speed and segmentation accuracy when evaluated on a retrospective OCT-A image dataset. Optical Coherence Tomography Angiography Foveal Avascular Zone Vessels Drop Prevention of blindness. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 12 Aug, 2025 Reviewers invited by journal 12 Aug, 2025 Editor assigned by journal 09 Aug, 2025 Submission checks completed at journal 09 Aug, 2025 First submitted to journal 07 Aug, 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-7315531","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":499574348,"identity":"25ba310d-1500-4175-8546-47e924560ef1","order_by":0,"name":"Arpan Chandra","email":"","orcid":"","institution":"National Institute of Technology Durgapur","correspondingAuthor":false,"prefix":"","firstName":"Arpan","middleName":"","lastName":"Chandra","suffix":""},{"id":499574349,"identity":"e9b21acf-9b81-410f-b6a8-cba6545e1ab0","order_by":1,"name":"Poulomi Mukherjee","email":"","orcid":"","institution":"University Of Engineering and Management","correspondingAuthor":false,"prefix":"","firstName":"Poulomi","middleName":"","lastName":"Mukherjee","suffix":""},{"id":499574350,"identity":"44b01e57-1f29-4e93-bb49-722398eb8403","order_by":2,"name":"Debolina Banerjee","email":"","orcid":"","institution":"Calcutta National Medical College and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Debolina","middleName":"","lastName":"Banerjee","suffix":""},{"id":499574351,"identity":"a04ca2b1-f070-42e4-b2d9-c5fd7f71d06c","order_by":3,"name":"Anupama Mukherjee","email":"","orcid":"","institution":"Calcutta National Medical College and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Anupama","middleName":"","lastName":"Mukherjee","suffix":""},{"id":499574352,"identity":"ced8c444-d7d7-4bbe-8222-8d4b0d0e156c","order_by":4,"name":"Sandeep Patra","email":"","orcid":"","institution":"National Institute of Technology Durgapur","correspondingAuthor":false,"prefix":"","firstName":"Sandeep","middleName":"","lastName":"Patra","suffix":""},{"id":499574353,"identity":"13c6eac8-0691-463f-bfb4-6b26940f225a","order_by":5,"name":"Sambuddha Ghosh","email":"","orcid":"","institution":"Calcutta National Medical College and Hospital","correspondingAuthor":false,"prefix":"","firstName":"Sambuddha","middleName":"","lastName":"Ghosh","suffix":""},{"id":499574354,"identity":"d02695ff-3605-40f6-89cd-ff1335a4c815","order_by":6,"name":"Ashis Kumar Dhara","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDACHgYzKIv5AEMCAzOUY0CUFrYEhoQE0rTwAJXBteAB/D2Htz34uceOgZ+959uDhz+s7bYzMD/8wFBwB6cWibNt5YY9z5IZJHvObjdISEhP3tnAZizBYPAMtzXnecwkeA4wMxjcyN0mkZBwONngAMipBodx6pAHapH8c6Cewf7+m2dQLezf8GoxONtjJs1z4DCDgQQPG0iLncEBHvy2GJ45ViYtc+A4j8SZNDOJhLT0BMtmnmKJBDxa5M4kb5N8c6Bajr/98DPJHzbW9ubs7Rs/fPiDWwsM8MAYiRtAUZNAUAMSsMcX76NgFIyCUTAyAQD9yFCOzX1f0gAAAABJRU5ErkJggg==","orcid":"","institution":"National Institute of Technology Durgapur","correspondingAuthor":true,"prefix":"","firstName":"Ashis","middleName":"Kumar","lastName":"Dhara","suffix":""}],"badges":[],"createdAt":"2025-08-07 06:53:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7315531/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7315531/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89465762,"identity":"4227be1f-25f1-4775-8c10-6dd06ec52607","added_by":"auto","created_at":"2025-08-20 08:32:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2381513,"visible":true,"origin":"","legend":"","description":"","filename":"FAZSegmentation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7315531/v1_covered_a255c567-3f8d-4848-a80c-26b3a8feb22f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Computer-aided Segmentation of Foveal Avascular Zone in OCT-A Images","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"signal-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sivp","sideBox":"Learn more about [Signal, Image and Video Processing](http://link.springer.com/journal/11760)","snPcode":"11760","submissionUrl":"https://submission.nature.com/new-submission/11760/3","title":"Signal, Image and Video Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Optical Coherence Tomography Angiography, Foveal Avascular Zone, Vessels Drop, Prevention of blindness.","lastPublishedDoi":"10.21203/rs.3.rs-7315531/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7315531/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrecise segmentation of the foveal avascular zone (FAZ) is critical because FAZ size and integrity are significant predictors of retinal health and visual acuity. FAZ area measurement holds substantial research value, as it provides additional information that can be used to develop new treatment modalities. Quantitative evaluation of the FAZ can detect early retinal microvascular alterations that are not yet symptomatic. In this paper, a computationally light deep neural network structure is built for the segmentation of FAZ in OCT-A images. The model should be computationally light and have high accuracy, thus being appropriately applied in clinical scenarios and deployed in environments with limited resources. Our structure outperforms traditional structures in both speed and segmentation accuracy when evaluated on a retrospective OCT-A image dataset.\u003c/p\u003e","manuscriptTitle":"Computer-aided Segmentation of Foveal Avascular Zone in OCT-A Images","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-20 08:00:21","doi":"10.21203/rs.3.rs-7315531/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-12T19:24:02+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-12T19:23:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-09T12:26:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-09T12:26:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Signal, Image and Video Processing","date":"2025-08-07T06:49:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"signal-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sivp","sideBox":"Learn more about [Signal, Image and Video Processing](http://link.springer.com/journal/11760)","snPcode":"11760","submissionUrl":"https://submission.nature.com/new-submission/11760/3","title":"Signal, Image and Video Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"72f5f80b-4a4d-4177-b47d-c263c135cdca","owner":[],"postedDate":"August 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-03T05:53:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-20 08:00:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7315531","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7315531","identity":"rs-7315531","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}