{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T08:48:38Z","timestamp":1791881318722,"version":"4.3.4"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T00:00:00Z","timestamp":1791849600000},"content-version":"vor","delay-in-days":91,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100000090","name":"United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs","doi-asserted-by":"publisher","award":["W81XWH-22-1-0803"],"award-info":[{"award-number":["W81XWH-22-1-0803"]}],"id":[{"id":"10.13039\/100000090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000090","name":"United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs","doi-asserted-by":"publisher","award":["W81XWH-22-1-0803"],"award-info":[{"award-number":["W81XWH-22-1-0803"]}],"id":[{"id":"10.13039\/100000090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000090","name":"United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs","doi-asserted-by":"publisher","award":["W81XWH-22-1-0803"],"award-info":[{"award-number":["W81XWH-22-1-0803"]}],"id":[{"id":"10.13039\/100000090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000090","name":"United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs","doi-asserted-by":"publisher","award":["W81XWH-22-1-0803"],"award-info":[{"award-number":["W81XWH-22-1-0803"]}],"id":[{"id":"10.13039\/100000090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000090","name":"United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs","doi-asserted-by":"publisher","award":["W81XWH-22-1-0803"],"award-info":[{"award-number":["W81XWH-22-1-0803"]}],"id":[{"id":"10.13039\/100000090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000090","name":"United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs","doi-asserted-by":"publisher","award":["W81XWH-22-1-0803"],"award-info":[{"award-number":["W81XWH-22-1-0803"]}],"id":[{"id":"10.13039\/100000090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000090","name":"United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs","doi-asserted-by":"publisher","award":["W81XWH-22-1-0803"],"award-info":[{"award-number":["W81XWH-22-1-0803"]}],"id":[{"id":"10.13039\/100000090","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Data"],"DOI":"10.1038\/s41597-026-07453-3","type":"journal-article","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T17:00:01Z","timestamp":1784048401000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ERDES: A Benchmark Video Dataset for Retinal Detachment and Macular Status Classification in Ocular Ultrasound"],"prefix":"10.1038","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7700-0091","authenticated-orcid":false,"given":"Yasemin","family":"Ozkut","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pouyan","family":"Navard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Srikar","family":"Adhikari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elaine","family":"Situ-LaCasse","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Josie","family":"Acu\u00f1a","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrienne A","family":"Yarnish","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alper","family":"Yilmaz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,14]]},"reference":[{"key":"7453_CR1","first-page":"0710","volume":"2014","author":"D Steel","year":"2014","unstructured":"Steel, D. Retinal detachment. BMJ Clinical Evidence 2014, 0710 (2014).","journal-title":"BMJ Clinical Evidence"},{"key":"7453_CR2","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1038\/sj.eye.6700197","volume":"16","author":"NG Ghazi","year":"2002","unstructured":"Ghazi, N. G. & Green, W. R. Pathology and pathogenesis of retinal detachment. Eye 16, 411\u2013421, https:\/\/doi.org\/10.1038\/sj.eye.6700197 (2002).","journal-title":"Eye"},{"key":"7453_CR3","first-page":"1691","volume":"69","author":"RF Gariano","year":"2004","unstructured":"Gariano, R. F. & Kim, C.-H. Evaluation and management of suspected retinal detachment. American Family Physician 69, 1691\u20131699 (2004).","journal-title":"American Family Physician"},{"key":"7453_CR4","doi-asserted-by":"publisher","first-page":"371\u2013382.e1","DOI":"10.1016\/j.ajo.2009.11.022","volume":"149","author":"MW Johnson","year":"2010","unstructured":"Johnson, M. W. Posterior vitreous detachment: evolution and complications of its early stages. American Journal of Ophthalmology 149, 371\u2013382.e1, https:\/\/doi.org\/10.1016\/j.ajo.2009.11.022 (2010).","journal-title":"American Journal of Ophthalmology"},{"key":"7453_CR5","unstructured":"Ahmed, F. & Tripathy, K. Posterior Vitreous Detachment. in StatPearls [Internet] (StatPearls Publishing, 2023)."},{"key":"7453_CR6","doi-asserted-by":"publisher","first-page":"2243","DOI":"10.1001\/jama.2009.1714","volume":"302","author":"H Hollands","year":"2009","unstructured":"Hollands, H. et al. Acute-onset floaters and flashes: is this patient at risk for retinal detachment? JAMA 302, 2243\u20132249, https:\/\/doi.org\/10.1001\/jama.2009.1714 (2009).","journal-title":"JAMA"},{"key":"7453_CR7","unstructured":"Wykoff, C. C., Smiddy, W. E., Lakhanpal, R. R. & Albini, T. Macula-on detachments can be managed with selectively urgent timing. Retina Today https:\/\/retinatoday.com\/articles\/2010-sept\/surgical-updates-macula-on-detachments-can-be-managed-with-selectively-urgent-timing (2010)."},{"key":"7453_CR8","doi-asserted-by":"publisher","first-page":"e146","DOI":"10.1016\/j.jemermed.2021.07.034","volume":"61","author":"R Subramony","year":"2021","unstructured":"Subramony, R., Lin, L. C., Knight, D. K., Aminlari, A. & Belovarski, I. Bilateral retinal detachments in a healthy 22-year-old woman after Moderna SARS-CoV-2 vaccination. J Emerg Med. 61, e146\u2013e150, https:\/\/doi.org\/10.1016\/j.jemermed.2021.07.034 (2021).","journal-title":"J Emerg Med."},{"key":"7453_CR9","doi-asserted-by":"publisher","first-page":"100","DOI":"10.4103\/2008-322X.180696","volume":"11","author":"S Mahmoudi","year":"2016","unstructured":"Mahmoudi, S. & Almony, A. Macula-sparing rhegmatogenous retinal detachment: is emergent surgery necessary? J Ophthalmic Vis Res. 11, 100\u2013107, https:\/\/doi.org\/10.4103\/2008-322X.180696 (2016).","journal-title":"J Ophthalmic Vis Res."},{"key":"7453_CR10","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1038\/s41433-020-01154-w","volume":"35","author":"A Grabowska","year":"2021","unstructured":"Grabowska, A., Neffendorf, J. E., Yorston, D. & Williamson, T. H. Urgency of retinal detachment repair: is it time to re-think our priorities? Eye 35, 1035\u20131036, https:\/\/doi.org\/10.1038\/s41433-020-01154-w (2021).","journal-title":"Eye"},{"key":"7453_CR11","unstructured":"Wang, D. & Rizzuti, A. Eye Trauma Imaging. in StatPearls [Internet] (StatPearls Publishing, 2023)."},{"key":"7453_CR12","doi-asserted-by":"publisher","DOI":"10.1186\/s13054-021-03466-z","volume":"25","author":"L Zieleskiewicz","year":"2021","unstructured":"Zieleskiewicz, L. et al. Bedside POCUS during ward emergencies is associated with improved diagnosis and outcome. Critical Care 25, 34, https:\/\/doi.org\/10.1186\/s13054-021-03466-z (2021).","journal-title":"Critical Care"},{"key":"7453_CR13","doi-asserted-by":"publisher","first-page":"e1921460","DOI":"10.1001\/jamanetworkopen.2019.21460","volume":"3","author":"SL Propst","year":"2020","unstructured":"Propst, S. L. et al. Ocular Point-of-Care Ultrasonography to Diagnose Posterior Chamber Abnormalities: A Systematic Review and Meta-analysis. JAMA Network Open 3, e1921460, https:\/\/doi.org\/10.1001\/jamanetworkopen.2019.21460 (2020).","journal-title":"JAMA Network Open"},{"key":"7453_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1167\/tvst.13.4.1","volume":"13","author":"M Christ","year":"2024","unstructured":"Christ, M. et al. Deep learning-based automated detection of retinal breaks and detachments on fundus photography. Trans. Vis. Sci. Tech. 13, 1, https:\/\/doi.org\/10.1167\/tvst.13.4.1 (2024).","journal-title":"Trans. Vis. Sci. Tech."},{"key":"7453_CR15","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1167\/tvst.14.2.26","volume":"14","author":"O Caki","year":"2025","unstructured":"Caki, O. et al. Automated Detection of Retinal Detachment Using Deep Learning-Based Segmentation on Ocular Ultrasonography Images. Trans. Vis. Sci. Tech. 14, 26, https:\/\/doi.org\/10.1167\/tvst.14.2.26 (2025).","journal-title":"Trans. Vis. Sci. Tech."},{"key":"7453_CR16","doi-asserted-by":"publisher","unstructured":"Yadav, S., Roy, N. K., Sharma, N. & Murugan, R. Classification of retinal detachment using deep learning through retinal fundus images. in 2022 IEEE India Council International Subsections Conference (INDISCON) 1\u20136, https:\/\/doi.org\/10.1109\/INDISCON54605.2022.9862901 (IEEE, 2022).","DOI":"10.1109\/INDISCON54605.2022.9862901"},{"key":"7453_CR17","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1038\/s42003-019-0730-x","volume":"3","author":"Z Li","year":"2020","unstructured":"Li, Z. et al. Deep learning for detecting retinal detachment and discerning macular status using ultra-widefield fundus images. Communications biology 3, 15, https:\/\/doi.org\/10.1038\/s42003-019-0730-x (2020).","journal-title":"Communications biology"},{"key":"7453_CR18","doi-asserted-by":"publisher","unstructured":"Ozkut, Y. et al. ERDES: A Benchmark Video Dataset for Retinal Detachment and Macular Status Classification in Ocular Ultrasound. Zenodo https:\/\/doi.org\/10.5281\/zenodo.18644370 (2026).","DOI":"10.5281\/zenodo.18644370"},{"key":"7453_CR19","doi-asserted-by":"publisher","unstructured":"Hara, K., Kataoka, H. & Satoh, Y. Can spatiotemporal 3D CNNs retrace the history of 2D CNNs and ImageNet? Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 6546\u20136555, https:\/\/doi.org\/10.1109\/CVPR.2018.00685 (2018).","DOI":"10.1109\/CVPR.2018.00685"},{"key":"7453_CR20","doi-asserted-by":"publisher","unstructured":"Cicek, O., Abdulkadir, A., Lienkamp, S. S., Brox, T. & Ronneberger, O. 3D U-Net: learning dense volumetric segmentation from sparse annotation. in Medical Image Computing and Computer-Assisted Intervention Vol. 9901, 424\u2013432, https:\/\/doi.org\/10.1007\/978-3-319-46723-8_49 (Springer, 2016).","DOI":"10.1007\/978-3-319-46723-8_49"},{"key":"7453_CR21","doi-asserted-by":"publisher","unstructured":"Milletari, F., Navab, N. & Ahmadi, S.-A. V-net: Fully convolutional neural networks for volumetric medical image segmentation. in Fourth International Conference on 3D Vision (3DV) 565\u2013571, https:\/\/doi.org\/10.1109\/3DV.2016.79 (IEEE, 2016).","DOI":"10.1109\/3DV.2016.79"},{"key":"7453_CR22","doi-asserted-by":"publisher","unstructured":"Zhou, Z., Rahman Siddiquee, M. M., Tajbakhsh, N. & Liang, J. Unet++: A nested u-net architecture for medical image segmentation. in Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support Vol. 11045, 3\u201311, https:\/\/doi.org\/10.1007\/978-3-030-00889-5_1 (Springer, 2018).","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"7453_CR23","doi-asserted-by":"publisher","unstructured":"Hu, J., Shen, L. & Sun, G. Squeeze-and-excitation networks. in IEEE\/CVF Conference on Computer Vision and Pattern Recognition 7132\u20137141, https:\/\/doi.org\/10.1109\/CVPR.2018.00745 (2018).","DOI":"10.1109\/CVPR.2018.00745"},{"key":"7453_CR24","doi-asserted-by":"publisher","unstructured":"Hatamizadeh, A. et al. Swin UNETR: Swin transformers for semantic segmentation of brain tumors in MRI images. in Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries Vol. 12962, 272\u2013284, https:\/\/doi.org\/10.1007\/978-3-031-08999-2_22 (Springer, 2022).","DOI":"10.1007\/978-3-031-08999-2_22"},{"key":"7453_CR25","doi-asserted-by":"publisher","unstructured":"Hatamizadeh, A. et al. UNETR: Transformers for 3D medical image segmentation. in IEEE\/CVF Winter Conference on Applications of Computer Vision 1748\u20131758, https:\/\/doi.org\/10.1109\/WACV51458.2022.00181 (2022).","DOI":"10.1109\/WACV51458.2022.00181"},{"key":"7453_CR26","unstructured":"Dosovitskiy, A. et al. An image is worth 16\u00a0\u00d7\u00a016 words: Transformers for image recognition at scale. in International Conference on Learning Representations (2021)."},{"key":"7453_CR27","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.ajem.2017.10.010","volume":"36","author":"N Baker","year":"2018","unstructured":"Baker, N. et al. Can emergency physicians accurately distinguish retinal detachment from posterior vitreous detachment with point-of-care ocular ultrasound? American Journal of Emergency Medicine 36, 774\u2013776, https:\/\/doi.org\/10.1016\/j.ajem.2017.10.010 (2018).","journal-title":"American Journal of Emergency Medicine"},{"key":"7453_CR28","unstructured":"Cardoso, M. J. et al. MONAI: An open-source framework for deep learning in healthcare. Preprint at https:\/\/arxiv.org\/abs\/2211.02701 (2022)."},{"key":"7453_CR29","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1167\/tvst.10.4.22","volume":"10","author":"D Chen","year":"2021","unstructured":"Chen, D. et al. A Deep Learning Model for Screening Multiple Abnormal Findings in Ophthalmic Ultrasonography (With Video). Trans. Vis. Sci. Tech. 10, 22, https:\/\/doi.org\/10.1167\/tvst.10.4.22 (2021).","journal-title":"Trans. Vis. Sci. Tech."},{"key":"7453_CR30","doi-asserted-by":"publisher","first-page":"2645","DOI":"10.1007\/s40123-024-01009-7","volume":"13","author":"X Ye","year":"2024","unstructured":"Ye, X. et al. Ocular disease detection with deep learning applied to ocular B-scan ultrasound images. Ophthalmol. Ther. 13, 2645\u20132659, https:\/\/doi.org\/10.1007\/s40123-024-01009-7 (2024).","journal-title":"Ophthalmol. Ther."},{"key":"7453_CR31","doi-asserted-by":"publisher","first-page":"103061","DOI":"10.1016\/j.artmed.2025.103317","volume":"171","author":"J Wang","year":"2025","unstructured":"Wang, J. et al. A labeled ophthalmic ultrasound dataset with medical report generation based on cross-modal deep learning. Artif. Intell. Med. 171, 103061, https:\/\/doi.org\/10.1016\/j.artmed.2025.103317 (2025).","journal-title":"Artif. Intell. Med."},{"key":"7453_CR32","doi-asserted-by":"publisher","unstructured":"Toyama, N., Hidaka, T., Tamura, H. & Ikeda, Y. Deep learning-based detection of retinal detachment with vitreous hemorrhage in ocular ultrasound images. Sci. Rep. https:\/\/doi.org\/10.1038\/s41598-026-38272-6 (2026).","DOI":"10.1038\/s41598-026-38272-6"}],"container-title":["Scientific Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07453-3","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07453-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07453-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T08:06:20Z","timestamp":1791878780000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07453-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,14]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["7453"],"URL":"https:\/\/doi.org\/10.1038\/s41597-026-07453-3","relation":{},"ISSN":["2052-4463"],"issn-type":[{"value":"2052-4463","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,14]]},"assertion":[{"value":"12 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no competing interests. There are no financial, personal or professional conflicts that could have influenced the design, execution, interpretation, or publication of this research. The authors affirm that the integrity of the research was not compromised by external interests or relationships and that all contributions were made with the aim of advancing scientific knowledge.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Ethics"}}],"article-number":"1415"}}