Thermal diffusion–based subsurface Depth Estimation in Active Infrared Thermography Using Thermal Signal Reconstruction and Deep Learning

Thermal diffusion–based subsurface Depth Estimation in Active Infrared Thermography Using Thermal Signal Reconstruction and Deep Learning | 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 Thermal diffusion–based subsurface Depth Estimation in Active Infrared Thermography Using Thermal Signal Reconstruction and Deep Learning Ramyadevi Ramaswamy, Emerson Raja Joseph, Senthil Arumugam Muthukumaraswamy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8503061/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 Breast cancer remains one of the most prevalent malignancies worldwide, with early detection being critical for improved patient outcomes. Infrared thermography offers a non-invasive, radiation-free technique to monitor physiological changes associated with malignancies, capturing subtle heat variations on the skin surface. In this study, we present an integrated approach combining Thermographic Signal Reconstruction (TSR), automatic region-of-interest (ROI) detection, and deep learning for precise depth estimation in tissue-mimicking phantoms embedded with resistive heat sources. Variable-frame thermal sequences are acquired using a long-wave infrared camera, and TSR is applied with shape-safe reconstruction to model surface temperature decay. Automatic ROI selection identifies regions exhibiting maximum thermal contrast, and second-derivative analysis with sub-frame quadratic interpolation extracts peak-time signals. Peak-time versus depth is analyzed using log–log regression weighted by signal-to-noise ratio (SNR). To further enhance prediction accuracy, a lightweight 3D convolutional neural network (3D-CNN) is trained on TSR-processed sequences, and Bayesian fusion of TSR and CNN outputs yields final depth estimates. The method achieves over 97% accuracy across multiple phantom depths, with Bland–Altman analysis confirming high agreement between predicted and true depths. Multi-depth decay curves, log–log peak-time plots, and confidence intervals demonstrate robust performance across variable thermal sequences. This pipeline provides a reliable framework for early breast cancer detection in a controlled phantom setting, and the methodology can be extended to clinical thermography applications, offering a rapid, non-contact, and interpretable diagnostic tool. Biological sciences/Cancer Biological sciences/Computational biology and bioinformatics Physical sciences/Engineering Physical sciences/Mathematics and computing Active Dynamic Thermography Thermographic Signal Reconstruction (TSR) Thermal Diffusion Modeling Non-Invasive Diagnostic Imaging Subsurface anomaly detection 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-8503061","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":577070212,"identity":"57db0041-2bcf-41fa-9d31-8cc1196234f6","order_by":0,"name":"Ramyadevi Ramaswamy","email":"","orcid":"","institution":"SRM Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ramyadevi","middleName":"","lastName":"Ramaswamy","suffix":""},{"id":577070213,"identity":"3711cc8d-2254-45b9-80aa-4a484365b025","order_by":1,"name":"Emerson Raja Joseph","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYJCDBIYPEIYB8VoYZ5CqhYGZhxgt/GKHj338UXGHwbz9wMPPtjnbEhvYm7dJMOYcxqlFcnZa8myeM88YZM4kJEvnbrud2MBzrEyCcRtuLQa3c4yZGdsOM0gwJCRAtEjkmOHVYn87/zPjT5AW/gfJvy1BWuTf4NdiIJ3DzMAL0iKRkCbNCLaFB78Widtpxsw8Zw7zSEg8SLPs3XbbuI0nrdgicVs6Ti38s5MfM/6oOCwnwZ+TfOPnttuy/eyHN974uM0apxYYAMYITwKYxQYiEhiaCWoBAvYDyLw6YrSMglEwCkbByAAAsh9S8mAjWScAAAAASUVORK5CYII=","orcid":"","institution":"Multimedia University","correspondingAuthor":true,"prefix":"","firstName":"Emerson","middleName":"Raja","lastName":"Joseph","suffix":""},{"id":577070214,"identity":"f9327eaa-4c18-4d04-adb0-80e5ceaea677","order_by":2,"name":"Senthil Arumugam Muthukumaraswamy","email":"","orcid":"","institution":"Heriot-Watt University Dubai","correspondingAuthor":false,"prefix":"","firstName":"Senthil","middleName":"Arumugam","lastName":"Muthukumaraswamy","suffix":""}],"badges":[],"createdAt":"2026-01-02 19:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8503061/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8503061/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100671295,"identity":"1e4abf74-499e-46ea-9d6d-a96e57831f0a","added_by":"auto","created_at":"2026-01-20 10:30:52","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1688933,"visible":true,"origin":"","legend":"","description":"","filename":"Journal1TSRActiveThermography.docx","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/5837c1475cc883128ee71206.docx"},{"id":100671496,"identity":"9f160359-4eb0-40b1-b778-e761f26e7299","added_by":"auto","created_at":"2026-01-20 10:32:32","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6419,"visible":true,"origin":"","legend":"","description":"","filename":"6f539e76941c47e2b0a3d7fdeab104dd.json","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/89ffc2dc786d1aede8c7bc16.json"},{"id":100671118,"identity":"a8abe7ad-b699-4dbd-bc5c-5a6ac0b39c95","added_by":"auto","created_at":"2026-01-20 10:29:54","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":109855,"visible":true,"origin":"","legend":"","description":"","filename":"6f539e76941c47e2b0a3d7fdeab104dd1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/a22cd906e07a5b23a9a7cd7d.xml"},{"id":100670947,"identity":"f5372a95-a721-48d7-bd9c-15a6201e15bb","added_by":"auto","created_at":"2026-01-20 10:27:30","extension":"jpeg","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":174122,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/9777d41c5f43fca642878024.jpeg"},{"id":100671501,"identity":"b33d0391-3fd8-4a4b-b343-c9032c153f89","added_by":"auto","created_at":"2026-01-20 10:32:43","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":92462,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/3a89e1a6154e2c43b0f2b1b6.png"},{"id":100671288,"identity":"10014ac5-de8a-4712-a8f4-7e86fa36a0a5","added_by":"auto","created_at":"2026-01-20 10:30:48","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152407,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/6d859a0e0acb6ef4905fd385.png"},{"id":100671498,"identity":"97eec723-1d63-4bad-8673-74c8f0c1c017","added_by":"auto","created_at":"2026-01-20 10:32:40","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":53067,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/22001a9f856e5a0a9479b515.png"},{"id":100670949,"identity":"8b7b44d0-fa22-458b-9ebf-9ad9cd600125","added_by":"auto","created_at":"2026-01-20 10:27:35","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":669856,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/77af0195dde15b9651507ed4.png"},{"id":100671048,"identity":"bbb86345-a2b9-4582-a138-1668b81b7617","added_by":"auto","created_at":"2026-01-20 10:29:24","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":146154,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/f17ba955264810691c5e7e87.png"},{"id":100671351,"identity":"fbad883c-ed5b-414e-a6b9-4dc095adb0bc","added_by":"auto","created_at":"2026-01-20 10:31:11","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95368,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/9d8bc64a39280d27f9d5e66f.png"},{"id":100671586,"identity":"16dc0605-7390-4940-9a25-c5835853f54d","added_by":"auto","created_at":"2026-01-20 10:33:13","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":85288,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/a76b510cde988bbdb3d9f43b.png"},{"id":100671030,"identity":"213b4f0e-5d2b-484d-9d84-337016f940c0","added_by":"auto","created_at":"2026-01-20 10:29:04","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":187410,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/aa7733a7112bdee7d7f07c65.png"},{"id":100671061,"identity":"0f0e6053-8269-465f-a248-0563637db60f","added_by":"auto","created_at":"2026-01-20 10:29:25","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95698,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/69f965ae2b4f762a617e83d0.png"},{"id":100671027,"identity":"aa962fd3-c7f9-4adb-be7d-d4cb3059bc81","added_by":"auto","created_at":"2026-01-20 10:28:56","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78545,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/82c57554341a53598e6f0bdd.png"},{"id":100671162,"identity":"bb96f2ea-ca19-4bd7-a8fb-d8d4fa6e9410","added_by":"auto","created_at":"2026-01-20 10:30:24","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":28011,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/457bca3da6ee239425e60f1c.png"},{"id":100671019,"identity":"4fb77252-2321-472f-a6e9-171c8431cfa3","added_by":"auto","created_at":"2026-01-20 10:28:37","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":27205,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/7c831221a41167823ea70a3f.png"},{"id":100671285,"identity":"946babbd-afc0-4dc1-a495-862ef46538bc","added_by":"auto","created_at":"2026-01-20 10:30:44","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":17386,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/8344b00974cdde951ea8f210.png"},{"id":100671636,"identity":"7832e7ed-fd8d-4c50-bce5-c8d631d60ba4","added_by":"auto","created_at":"2026-01-20 10:33:42","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":49771,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/70c0428238b41317e6759e5f.png"},{"id":100671192,"identity":"028e6af5-c530-4742-8a88-4a7ec36cd7ad","added_by":"auto","created_at":"2026-01-20 10:30:27","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":28589,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/cfad6b6bfdbc0dead9c0493c.png"},{"id":100671071,"identity":"ef3bf7bc-961e-4561-be51-69c756cfac3c","added_by":"auto","created_at":"2026-01-20 10:29:42","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":29127,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/6e1ae9eedd7d4ab97dce29b6.png"},{"id":100671063,"identity":"b02ee0f8-9269-4d80-933d-46a1f5928472","added_by":"auto","created_at":"2026-01-20 10:29:31","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":27018,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/180bb8ea8483b72418743d19.png"},{"id":100671452,"identity":"61d7f322-d751-4b41-911b-4e3b9681b0ef","added_by":"auto","created_at":"2026-01-20 10:31:33","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":36654,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/d3591d631d9fdb333ca1041d.png"},{"id":100671264,"identity":"eb455211-73aa-4c9e-9b93-074f44708a4f","added_by":"auto","created_at":"2026-01-20 10:30:39","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":27969,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/a25229dd3ca15f4ebd2e2fad.png"},{"id":100671353,"identity":"b6f4152b-33ce-4494-8958-69a49974329a","added_by":"auto","created_at":"2026-01-20 10:31:13","extension":"xml","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":109297,"visible":true,"origin":"","legend":"","description":"","filename":"6f539e76941c47e2b0a3d7fdeab104dd1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/5e3b998fec3d804aba81e47d.xml"},{"id":100671107,"identity":"950596d4-f409-42d2-91e5-8eda31a10b48","added_by":"auto","created_at":"2026-01-20 10:29:48","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":125088,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1/ac2b9b6142609a5f8976e8d8.html"},{"id":102313558,"identity":"49d3a034-48cd-4fdd-acab-d29204e211a5","added_by":"auto","created_at":"2026-02-10 12:12:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1006465,"visible":true,"origin":"","legend":"","description":"","filename":"Journal1TSRActiveThermography.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8503061/v1_covered_faf05261-f303-4580-81ef-3bee61600d01.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Thermal diffusion–based subsurface Depth Estimation in Active Infrared Thermography Using Thermal Signal Reconstruction and Deep Learning","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":"Active Dynamic Thermography, Thermographic Signal Reconstruction (TSR), Thermal Diffusion Modeling, Non-Invasive Diagnostic Imaging, Subsurface anomaly detection","lastPublishedDoi":"10.21203/rs.3.rs-8503061/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8503061/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBreast cancer remains one of the most prevalent malignancies worldwide, with early detection being critical for improved patient outcomes. Infrared thermography offers a non-invasive, radiation-free technique to monitor physiological changes associated with malignancies, capturing subtle heat variations on the skin surface. In this study, we present an integrated approach combining Thermographic Signal Reconstruction (TSR), automatic region-of-interest (ROI) detection, and deep learning for precise depth estimation in tissue-mimicking phantoms embedded with resistive heat sources. Variable-frame thermal sequences are acquired using a long-wave infrared camera, and TSR is applied with shape-safe reconstruction to model surface temperature decay. Automatic ROI selection identifies regions exhibiting maximum thermal contrast, and second-derivative analysis with sub-frame quadratic interpolation extracts peak-time signals. Peak-time versus depth is analyzed using log\u0026ndash;log regression weighted by signal-to-noise ratio (SNR). To further enhance prediction accuracy, a lightweight 3D convolutional neural network (3D-CNN) is trained on TSR-processed sequences, and Bayesian fusion of TSR and CNN outputs yields final depth estimates. The method achieves over 97% accuracy across multiple phantom depths, with Bland\u0026ndash;Altman analysis confirming high agreement between predicted and true depths. Multi-depth decay curves, log\u0026ndash;log peak-time plots, and confidence intervals demonstrate robust performance across variable thermal sequences. This pipeline provides a reliable framework for early breast cancer detection in a controlled phantom setting, and the methodology can be extended to clinical thermography applications, offering a rapid, non-contact, and interpretable diagnostic tool.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"Thermal diffusion–based subsurface Depth Estimation in Active Infrared Thermography Using Thermal Signal Reconstruction and Deep Learning","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-20 09:12:48","doi":"10.21203/rs.3.rs-8503061/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"722a6826-f1d2-484e-9948-d9d62e013440","owner":[],"postedDate":"January 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61396460,"name":"Biological sciences/Cancer"},{"id":61396461,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":61396462,"name":"Physical sciences/Engineering"},{"id":61396463,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2026-02-10T12:12:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-20 09:12:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8503061","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8503061","identity":"rs-8503061","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}