{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T23:35:29Z","timestamp":1776900929471,"version":"3.51.2"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:00:00Z","timestamp":1776902400000},"content-version":"vor","delay-in-days":43,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100003130","name":"Fonds Wetenschappelijk Onderzoek","doi-asserted-by":"publisher","award":["12A8125N"],"award-info":[{"award-number":["12A8125N"]}],"id":[{"id":"10.13039\/501100003130","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-39665-3","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T17:04:44Z","timestamp":1773248684000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI driven interactive extraction of tomographic ultrasound imaging sequences for anal sphincter defects"],"prefix":"10.1038","volume":"16","author":[{"given":"Helena","family":"Williams","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bram","family":"Packet","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura","family":"Cattani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Susanne","family":"Housmans","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adela","family":"Samesova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucie","family":"Hympanova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Florian","family":"Ramakers","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hans Peter","family":"Dietz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"D\u2019hooge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom","family":"Vercauteren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Deprest","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,3,11]]},"reference":[{"key":"39665_CR1","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1186\/s12905-022-01915-7","volume":"22","author":"AL Stickelmann","year":"2022","unstructured":"Stickelmann, A. L. et al. Obstetric anal sphincter injuries (OASIS): using transperineal ultrasound (TPUS) for detecting, visualizing and monitoring the healing process. BMC Womens Health. 22, 339. https:\/\/doi.org\/10.1186\/s12905-022-01915-7 (2022).","journal-title":"BMC Womens Health"},{"key":"39665_CR2","doi-asserted-by":"publisher","first-page":"1420","DOI":"10.1111\/1471-0528.17820","volume":"131","author":"L Cattani","year":"2024","unstructured":"Cattani, L., Van Schoubroeck, D., De Bruyn, C., Ghesqui\u00e8re, S. & Deprest, J. Body image and pelvic floor dysfunction in pregnancy and postpartum: A prospective one-year follow-up cohort study. BJOG 131, 1420\u20131429. https:\/\/doi.org\/10.1111\/1471-0528.17820 (2024).","journal-title":"BJOG"},{"key":"39665_CR3","doi-asserted-by":"publisher","first-page":"e317","DOI":"10.1016\/s2214-109x(23)00454-0","volume":"12","author":"JP Vogel","year":"2024","unstructured":"Vogel, J. P. et al. Neglected medium-term and long-term consequences of labour and childbirth: a systematic analysis of the burden, recommended practices, and a way forward. Lancet Global Health. 12, e317\u2013e330. https:\/\/doi.org\/10.1016\/s2214-109x(23)00454-0 (2024).","journal-title":"Lancet Global Health"},{"key":"39665_CR4","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1002\/uog.26292","volume":"62","author":"B Packet","year":"2023","unstructured":"Packet, B. et al. Predictive factors for obstetric anal sphincter injury in primiparous women: systematic review and meta-analysis. Ultrasound Obstet. Gynecol. 62, 486\u2013496. https:\/\/doi.org\/10.1002\/uog.26292 (2023).","journal-title":"Ultrasound Obstet. Gynecol."},{"key":"39665_CR5","doi-asserted-by":"publisher","unstructured":"Bellussi, F. & Dietz, H. P. Postpartum ultrasound for the diagnosis of obstetrical anal sphincter injury. Am. J. Obstet. Gynecol. MFM. 3 https:\/\/doi.org\/10.1016\/j.ajogmf.2021.100421 (2021).","DOI":"10.1016\/j.ajogmf.2021.100421"},{"key":"39665_CR6","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1259\/bjr\/27314678","volume":"85","author":"Z Abdool","year":"2012","unstructured":"Abdool, Z., Sultan, A. H. & Thakar, R. Ultrasound imaging of the anal sphincter complex: a review. Br. J. Radiol. 85, 865\u2013875. https:\/\/doi.org\/10.1259\/bjr\/27314678 (2012).","journal-title":"Br. J. Radiol."},{"key":"39665_CR7","doi-asserted-by":"publisher","first-page":"1389","DOI":"10.1007\/s00192-019-03954-5","volume":"30","author":"AIUM\/IUGA practice parameter for the performance of Urogynecological ultrasound examinations","year":"2019","unstructured":"AIUM\/IUGA practice parameter for the performance of Urogynecological ultrasound examinations. Int. Urogynecol. J. 30, 1389\u20131400 https:\/\/doi.org\/10.1007\/s00192-019-03954-5 (2019).","journal-title":"Int. Urogynecol. J."},{"key":"39665_CR8","doi-asserted-by":"publisher","first-page":"1107","DOI":"10.1007\/s00192-019-04122-5","volume":"31","author":"L Cattani","year":"2020","unstructured":"Cattani, L. et al. Exo-anal imaging of the anal sphincter: a comparison between introital and transperineal image acquisition. Int. Urogynecol. J. 31, 1107\u20131113. https:\/\/doi.org\/10.1007\/s00192-019-04122-5 (2020).","journal-title":"Int. Urogynecol. J."},{"key":"39665_CR9","doi-asserted-by":"publisher","first-page":"793","DOI":"10.1002\/uog.24957","volume":"60","author":"NA Okeahialam","year":"2022","unstructured":"Okeahialam, N. A., Thakar, R. & Sultan, A. H. Comparison of diagnostic criteria for significant anal sphincter defects between endoanal and transperineal ultrasound. Ultrasound Obstet. Gynecol. 60, 793\u2013799. https:\/\/doi.org\/10.1002\/uog.24957 (2022).","journal-title":"Ultrasound Obstet. Gynecol."},{"key":"39665_CR10","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1002\/uog.12481","volume":"42","author":"RA Guzm\u00e1n Rojas","year":"2013","unstructured":"Guzm\u00e1n Rojas, R. A., Shek, K. L., Langer, S. M. & Dietz, H. P. Prevalence of anal sphincter injury in primiparous women. Ultrasound Obstet. Gynecol. 42, 461\u2013466. https:\/\/doi.org\/10.1002\/uog.12481 (2013).","journal-title":"Ultrasound Obstet. Gynecol."},{"key":"39665_CR11","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1002\/jum.14246","volume":"37","author":"HP Dietz","year":"2018","unstructured":"Dietz, H. P. Exoanal imaging of the anal sphincters. J. Ultrasound Med. 37, 263\u2013280. https:\/\/doi.org\/10.1002\/jum.14246 (2018).","journal-title":"J. Ultrasound Med."},{"key":"39665_CR12","doi-asserted-by":"publisher","first-page":"682","DOI":"10.3390\/diagnostics13040682","volume":"13","author":"D Carter","year":"2023","unstructured":"Carter, D., Ram, E. & Engel, T. Combined 3D endoanal ultrasound and transperineal ultrasound improves the detection of anal sphincter defects. Diagnostics 13, 682. https:\/\/doi.org\/10.3390\/diagnostics13040682 (2023).","journal-title":"Diagnostics"},{"key":"39665_CR13","doi-asserted-by":"publisher","first-page":"836","DOI":"10.1002\/uog.20175","volume":"53","author":"F Turel Fatakia","year":"2019","unstructured":"Turel Fatakia, F., Subramaniam, N., Bienkiewicz, J., Friedman, T. & Dietz, H. P. How repeatable is assessment of external anal sphincter trauma by exoanal 4D ultrasound? Ultrasound Obstet. Gynecol. 53, 836\u2013840. https:\/\/doi.org\/10.1002\/uog.20175 (2019).","journal-title":"Ultrasound Obstet. Gynecol."},{"key":"39665_CR14","doi-asserted-by":"crossref","unstructured":"Williams, H., Cattani, L., Vercauteren, T., Deprest, J. & D\u2019hooge, J. in Simplifying Medical Ultrasound: Second International Workshop, ASMUS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, Proceedings 35\u201344 (Springer-Verlag, Strasbourg, France, 2021). (2021).","DOI":"10.1007\/978-3-030-87583-1_4"},{"key":"39665_CR15","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1002\/uog.26238","volume":"62","author":"TG Day","year":"2023","unstructured":"Day, T. G. et al. Sonographer interaction with artificial intelligence: collaboration or conflict? Ultrasound Obstet. Gynecol. 62, 167\u2013174. https:\/\/doi.org\/10.1002\/uog.26238 (2023).","journal-title":"Ultrasound Obstet. Gynecol."},{"key":"39665_CR16","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","volume":"18","author":"F Isensee","year":"2021","unstructured":"Isensee, F., Jaeger, P. F., Kohl, S. A. A., Petersen, J. & Maier-Hein, K. H. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat. Methods. 18, 203\u2013211. https:\/\/doi.org\/10.1038\/s41592-020-01008-z (2021).","journal-title":"Nat. Methods"},{"key":"39665_CR17","doi-asserted-by":"publisher","first-page":"2198","DOI":"10.1109\/tmi.2019.2900516","volume":"38","author":"S Leclerc","year":"2019","unstructured":"Leclerc, S. et al. Deep learning for segmentation using an open Large-Scale dataset in 2D echocardiography. IEEE Trans. Med. Imaging. 38, 2198\u20132210. https:\/\/doi.org\/10.1109\/tmi.2019.2900516 (2019).","journal-title":"IEEE Trans. Med. Imaging"},{"key":"39665_CR18","doi-asserted-by":"publisher","first-page":"3470","DOI":"10.1016\/j.ultrasmedbio.2021.08.009","volume":"47","author":"H Williams","year":"2021","unstructured":"Williams, H. et al. Automatic extraction of hiatal dimensions in 3-D transperineal pelvic ultrasound recordings. Ultrasound Med. Biol. 47, 3470\u20133479. https:\/\/doi.org\/10.1016\/j.ultrasmedbio.2021.08.009 (2021).","journal-title":"Ultrasound Med. Biol."},{"issue":"S1","key":"39665_CR19","first-page":"193","volume":"32","author":"D HP","year":"2021","unstructured":"HP, D. & KL, S. Do we need individualized interslice intervals for exo-anal imaging of the anal canal? Int. Urogynecol. J. 32 (S1), 193 (2021).","journal-title":"Int. Urogynecol. J."},{"key":"39665_CR20","doi-asserted-by":"publisher","DOI":"10.1093\/bjrai\/ubae015","author":"A De Biase","year":"2024","unstructured":"De Biase, A. et al. Clinical adoption of deep learning target auto-segmentation for radiation therapy: challenges, clinical risks, and mitigation strategies. BJR|Artificial Intell. https:\/\/doi.org\/10.1093\/bjrai\/ubae015 (2024).","journal-title":"BJR|Artificial Intell."},{"key":"39665_CR21","unstructured":"Administration, U. S. F. & a., D. Good Machine Learning Practice for Medical Device Development: Guiding Principles, (2021). https:\/\/www.fda.gov\/medical-devices\/software-medical-device-samd\/good-machine-learning-practice-medical-device-development-guiding-principles."},{"key":"39665_CR22","unstructured":"Administration, U. S. F. & a., D. Transparency for Machine Learning-Enabled Medical Devices: Guiding Principles, (2024). https:\/\/www.fda.gov\/medical-devices\/software-medical-device-samd\/transparency-machine-learning-enabled-medical-devices-guiding-principles."},{"key":"39665_CR23","doi-asserted-by":"publisher","unstructured":"Aboy, M., Minssen, T. & Vayena, E. Navigating the EU AI act: implications for regulated digital medical products. Npj Digit. Med. 7 https:\/\/doi.org\/10.1038\/s41746-024-01232-3 (2024).","DOI":"10.1038\/s41746-024-01232-3"},{"key":"39665_CR24","doi-asserted-by":"crossref","unstructured":"Fenner, D. E. et al. Anatomic and physiologic measurements of the internal and external anal sphincters in normal females. Obstetrics & Gynecology 91 (1998).","DOI":"10.1016\/S0029-7844(97)00678-9"},{"key":"39665_CR25","unstructured":"De Gandra, S. M. et al. in International Urogynecol. Journal 1\u2013349 ."},{"key":"39665_CR26","doi-asserted-by":"publisher","unstructured":"Haenen, K., Packet, B., Deprest, J. & Williams, H. From novice to expert: Ai-Assistance improves external anal sphincter defect detection and workflow Efficiency- IUGA\/EUGA joint meeting 2025. IUGA 50th Annual Meeting \u2013 Barcelona June 18\u201321 2025 Int. Urogynecol. J. 36 (1-489). https:\/\/doi.org\/10.1007\/s00192-025-06257-0 (2025).","DOI":"10.1007\/s00192-025-06257-0"},{"key":"39665_CR27","doi-asserted-by":"publisher","unstructured":"Williams, H. et al. AI-Driven detection of external anal sphincter defects in transperineal Ultrasound - IUGA\/EUGA joint meeting 2025. IUGA 50th Annual Meeting \u2013 Barcelona June 18\u201321 2025 Int. Urogynecol. J. 36 (1-489). https:\/\/doi.org\/10.1007\/s00192-025-06257-0 (2025).","DOI":"10.1007\/s00192-025-06257-0"},{"key":"39665_CR28","doi-asserted-by":"publisher","first-page":"1673","DOI":"10.1002\/jum.16490","volume":"43","author":"L Cattani","year":"2024","unstructured":"Cattani, L. et al. Three-Dimensional transperineal ultrasound assessment of the anal sphincter immediately after vaginal birth: an exploratory study. J. Ultrasound Med. 43, 1673\u20131681. https:\/\/doi.org\/10.1002\/jum.16490 (2024).","journal-title":"J. Ultrasound Med."},{"key":"39665_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00192-023-05622-1","volume":"34","author":"E Bauters","year":"2023","unstructured":"Bauters, E. et al. IUGA scientific meeting 2023. Int. Urogynecol. J. 34, 1\u2013254. https:\/\/doi.org\/10.1007\/s00192-023-05622-1 (2023).","journal-title":"Int. Urogynecol. J."},{"key":"39665_CR30","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1002\/sam.11583","volume":"15","author":"VR Joseph","year":"2022","unstructured":"Joseph, V. R. Optimal ratio for data splitting. Stat. Anal. Data Mining: ASA Data Sci. J. 15, 531\u2013538. https:\/\/doi.org\/10.1002\/sam.11583 (2022).","journal-title":"Stat. Anal. Data Mining: ASA Data Sci. J."},{"key":"39665_CR31","doi-asserted-by":"publisher","unstructured":"Liu, X. et al. Towards more precise automatic analysis: a systematic review of deep learning-based multi-organ segmentation. Biomed. Eng. Online. 23 https:\/\/doi.org\/10.1186\/s12938-024-01238-8 (2024).","DOI":"10.1186\/s12938-024-01238-8"},{"key":"39665_CR32","unstructured":"Williams, H. et al. in 2023 IEEE International Ultrasonics Symposium (IUS). 1\u20134 (IEEE)."},{"key":"39665_CR33","doi-asserted-by":"publisher","first-page":"8923","DOI":"10.3390\/app13158923","volume":"13","author":"S Albert","year":"2023","unstructured":"Albert, S. et al. Comparison of image normalization methods for Multi-Site deep learning. Appl. Sci. 13, 8923 (2023).","journal-title":"Appl. Sci."},{"key":"39665_CR34","unstructured":"Pal, K. K. & Sudeep, K. S. in IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). (IEEE). (IEEE). (2016)."},{"key":"39665_CR35","unstructured":"Ramakers, F., Vercauteren, T., Deprest, J. & Williams, H. in IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2422\u20132431 (CVF Open access)."},{"key":"39665_CR36","unstructured":"HP, D. & KL, S. in Int Urogynecology Journal."},{"key":"39665_CR37","unstructured":"Cardoso, M. J. et al. Monai: An open-source framework for deep learning in healthcare. arXiv preprint arXiv:2211.02701 (2022)."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-39665-3","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-39665-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-39665-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T22:37:56Z","timestamp":1776897476000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-39665-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,11]]},"references-count":37,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["39665"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-39665-3","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,11]]},"assertion":[{"value":"21 November 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 February 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"H. P. Dietz - consults General Electric Medical and Materna, accepted reimbursement of travel costs and lecture fees from Mindray and General Electric Medical.T. Vercauteren - Chief Scientific Officer (CSO) at Hypervision Surgical J. Deprest and H. Williams (KU Leuven) - have had previous research service agreements with General Electric Healthcare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"13177"}}