Real-Time Spatiotemporal Denoising Volumetric Rendering in Three-Dimensional Visualization of Puncturing Navigation

Real-Time Spatiotemporal Denoising Volumetric Rendering in Three-Dimensional Visualization of Puncturing Navigation | 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 Real-Time Spatiotemporal Denoising Volumetric Rendering in Three-Dimensional Visualization of Puncturing Navigation Jing Li, Jie Zhou, Nanyan Shen, Yingjie Li, Ping Song, Yan Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4512330/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract In medical diagnosis and surgical treatment, particularly in tumor puncturing surgeries, the importance of three-dimensional visualization of medical data is increasingly recognized. Traditional two-dimensional imaging techniques are limited in spatial and depth perception. This study introduces a novel real-time spatiotemporal denoising volumetric rendering technique aimed at enhancing three-dimensional visualization in puncturing navigation systems. By analyzing existing volumetric rendering methods, a spatiotemporal filtering approach is proposed. This approach filters images rendered with one sample per pixel by calculating inter-frame motion vectors in the time domain and utilizing auxiliary features in the spatial domain. It effectively reduces the noise from Monte Carlo estimations and enhances the clarity of three-dimensional organ structures. This technique achieves real-time performance exceeding 30 Hz on commercial-grade Graphics Processing Units (GPUs). The real-time spatiotemporal denoising volumetric rendering significantly enhances the three-dimensional visualization quality in puncturing navigation systems, achieving a balance between high-quality rendering and real-time performance, meeting clinical needs. This technology also has broad application potential in medical training, surgical simulation, and remote collaboration. Three-Dimensional Visualization of Medical Data Percutaneous Navigation Real-Time Rendering Volume Rendering Spatiotemporal Denoising Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 01 Jun, 2024 Submission checks completed at journal 01 Jun, 2024 First submitted to journal 01 Jun, 2024 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. 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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-4512330","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":309401298,"identity":"4522bf71-4a46-464b-b877-2404e8036718","order_by":0,"name":"Jing Li","email":"","orcid":"","institution":"Shanghai University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Li","suffix":""},{"id":309401299,"identity":"e3ed4c80-9bf9-4efd-9090-8002d3bbbe85","order_by":1,"name":"Jie Zhou","email":"","orcid":"","institution":"Shanghai University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Zhou","suffix":""},{"id":309401300,"identity":"a10a4862-bc37-467d-98ff-2b81b437f57e","order_by":2,"name":"Nanyan Shen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYDACCSD+wHAAxDQgXgvjDJK1MPOQpEV+du8xaZs/dxIb2Ju3STDU3CGsxeDOuTTp3LZniQ08x8okGI49I0KLRI6ZdG7D4cQGIEOCseEwEQ6bAdRi8QeoRf4NkVoYbgC1MLCBbOEhUovBjRxjy962w8ZtPGnFFgnHiHOY4Y0ffw7L9rMf3njjQw0xDmNgYAElAAY2EJFAlAZgTH4gUuEoGAWjYBSMVAAARao5JJy5sFsAAAAASUVORK5CYII=","orcid":"","institution":"Shanghai University","correspondingAuthor":true,"prefix":"","firstName":"Nanyan","middleName":"","lastName":"Shen","suffix":""},{"id":309401302,"identity":"81ac3c66-ec2e-4e80-a3c4-b4f96fbabbd1","order_by":3,"name":"Yingjie Li","email":"","orcid":"","institution":"Shanghai University","correspondingAuthor":false,"prefix":"","firstName":"Yingjie","middleName":"","lastName":"Li","suffix":""},{"id":309401303,"identity":"032f6bc4-7fe4-41f3-8bbb-26e762ff94d8","order_by":4,"name":"Ping Song","email":"","orcid":"","institution":"Shanghai University","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Song","suffix":""},{"id":309401304,"identity":"ccc283cc-2ce8-4b41-a76b-cc2a57867f12","order_by":5,"name":"Yan Wang","email":"","orcid":"","institution":"Shanghai University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-06-01 06:57:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4512330/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4512330/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58328266,"identity":"8a2a9de0-b9b3-4a62-986b-7f741dacf363","added_by":"auto","created_at":"2024-06-14 03:01:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1230034,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4512330/v1_covered_31d2aa6c-132a-40ce-87e3-6eae3206f9f8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Real-Time Spatiotemporal Denoising Volumetric Rendering in Three-Dimensional Visualization of Puncturing Navigation","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":"the-visual-computer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tvcj","sideBox":"Learn more about [The Visual Computer](http://link.springer.com/journal/371)","snPcode":"371","submissionUrl":"https://submission.nature.com/new-submission/371/3","title":"The Visual Computer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Three-Dimensional Visualization of Medical Data, Percutaneous Navigation, Real-Time Rendering, Volume Rendering, Spatiotemporal Denoising","lastPublishedDoi":"10.21203/rs.3.rs-4512330/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4512330/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn medical diagnosis and surgical treatment, particularly in tumor puncturing surgeries, the importance of three-dimensional visualization of medical data is increasingly recognized. Traditional two-dimensional imaging techniques are limited in spatial and depth perception. This study introduces a novel real-time spatiotemporal denoising volumetric rendering technique aimed at enhancing three-dimensional visualization in puncturing navigation systems. By analyzing existing volumetric rendering methods, a spatiotemporal filtering approach is proposed. This approach filters images rendered with one sample per pixel by calculating inter-frame motion vectors in the time domain and utilizing auxiliary features in the spatial domain. It effectively reduces the noise from Monte Carlo estimations and enhances the clarity of three-dimensional organ structures. This technique achieves real-time performance exceeding 30 Hz on commercial-grade Graphics Processing Units (GPUs). 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