Object Detection as an Aid for Locating the Prostate in Surface-Based Abdominal Ultrasound Images

Object Detection as an Aid for Locating the Prostate in Surface-Based Abdominal Ultrasound 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 Article Object Detection as an Aid for Locating the Prostate in Surface-Based Abdominal Ultrasound Images Zion Tse, Rory Bennett, Tristan Barrett, Vincent Gnanapragasam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6211216/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2025 Read the published version in Communications Engineering → Version 1 posted You are reading this latest preprint version Abstract Automatic object detection is increasingly used in the medical field to great effect. It can be used to enhance clinical workflows before, during, and after diagnosis of various conditions. One example is prostate detection and size estimation, which can aid in triaging patients for prostate cancer through risk-stratification using prostate-specific antigen density. In this paper, a baseline prostate detection framework is presented, highlighting that current state-of-the-art object detections models can detect the prostate in difficult to interpret surface-based ultrasound images with high accuracy. A 5-fold cross-validation study returned intersection-over-union, precision, recall, F1, and average-precision values above 𝟎.𝟕 with real-time capabilities possible. Additionally, a simple size calculation based on the detection results shows high correlation with ground truth measurements, with Pearson Correlation Coefficients ranging from 𝟎.𝟓 to 𝟎.𝟖 for prostate volume estimates. These findings will contribute to the development of a real-time prostate detection and size estimation platform prostate cancer risk-stratification. Health sciences/Health care/Medical imaging/Ultrasonography Health sciences/Diseases/Cancer Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ObjectDetectionasanAidforLocatingtheProstateinSurfaceBasedAbdominalUltrasoundImagesSupplementaryMaterial.docx Supplementary Material Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2025 Read the published version in Communications Engineering → 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. 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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-6211216","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":430065538,"identity":"362eb0c1-02ef-4c06-a2aa-e3225a7600ba","order_by":0,"name":"Zion Tse","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYNCCCiBmhzANiFDODMRnoDTxWhjbSNEi38B/+MPHedbRBocZGD/8YDhsTFALYwMzm+TMbem5Gw4zMEv2MBw2I8JZzGzMvNsOg7QwSDMwHLYhqIWNgZn58985YC3Mv4nSwgO0R5qxAayFDWQLYYdJMDObSfYcS8+deZixzbLHIJ2w9+XbGx9/+FFjndt3vPnwjR8V1oYNBPUww0nGBuIiEkXjKBgFo2AUjAKsAADBXDJ0ypq1zAAAAABJRU5ErkJggg==","orcid":"","institution":"QMUL","correspondingAuthor":true,"prefix":"","firstName":"Zion","middleName":"","lastName":"Tse","suffix":""},{"id":430065539,"identity":"5147c808-5b20-4bf8-9a65-3f070a9ffc40","order_by":1,"name":"Rory Bennett","email":"","orcid":"","institution":"Queen Mary University of London","correspondingAuthor":false,"prefix":"","firstName":"Rory","middleName":"","lastName":"Bennett","suffix":""},{"id":430065540,"identity":"62a23f0e-3948-44a7-967a-2ae9ef0d0df2","order_by":2,"name":"Tristan Barrett","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Tristan","middleName":"","lastName":"Barrett","suffix":""},{"id":430065541,"identity":"905ae43b-a624-4e69-bf63-c7c3b0792adb","order_by":3,"name":"Vincent Gnanapragasam","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Vincent","middleName":"","lastName":"Gnanapragasam","suffix":""}],"badges":[],"createdAt":"2025-03-12 10:35:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6211216/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6211216/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s44172-025-00550-y","type":"published","date":"2025-11-28T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":98928009,"identity":"00823612-1988-4b81-bd6c-7c06552d0330","added_by":"auto","created_at":"2025-12-24 08:10:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1306727,"visible":true,"origin":"","legend":"","description":"","filename":"ObjectDetectionasanAidforLocatingtheProstateinSurfaceBasedAbdominalUltrasoundImages.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6211216/v1_covered_88a3f91a-dc33-4a1b-a754-c585de0fbac2.pdf"},{"id":79253035,"identity":"481976df-c86f-408d-b040-26726501261c","added_by":"auto","created_at":"2025-03-26 08:27:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17527,"visible":true,"origin":"","legend":"Supplementary Material","description":"","filename":"ObjectDetectionasanAidforLocatingtheProstateinSurfaceBasedAbdominalUltrasoundImagesSupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6211216/v1/d76e7095c51a6a25440826ca.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Object Detection as an Aid for Locating the Prostate in Surface-Based Abdominal Ultrasound Images","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6211216/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6211216/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAutomatic object detection is increasingly used in the medical field to great effect. 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