{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T15:07:17Z","timestamp":1786115237212,"version":"build-2736575974"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T00:00:00Z","timestamp":1785974400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T00:00:00Z","timestamp":1785974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100003252","name":"Lund University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003252","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Robotic Surg"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Accurate identification of anatomical structures is essential for safe congenital cardiac surgery and for the development of assistive robotic systems. However, scalable annotation of open-heart surgical video remains a major challenge due to dynamic tissue motion, occlusion, and anatomical variability. The aim of this study was to develop and evaluate a human-in-the-loop segmentation and tracking pipeline for congenital open-heart surgery videos. A dataset of 72 annotated video clips comprising 27,461 frames was created from routine recordings of congenital cardiac surgery. Independent tracking evaluation was performed on 6 video clips (2,400 frames) from three surgical cases that were not used for training or validation. A hybrid framework combining fine-tuned Segment Anything Model 2 (SAM 2) for propagation-based tracking and YOLOv11 for detection-based monitoring was implemented and evaluated. Fine-tuning improved temporal tracking performance compared with the pretrained model, increasing the mean IoU from 82.1% to 92.2% and the proportion of frames with IoU\u2009\u2265\u200990% from 48.2% to 72.3% on the independent evaluation dataset. A graphical user interface enabled efficient dataset creation, reducing annotation time by approximately 40-fold compared with manual tracing. This study demonstrates that domain-adapted foundation-model tracking can provide robust anatomical tracking in a dynamic open surgical environment and offers a scalable framework for future assistive and robotic cardiac applications.<\/jats:p>","DOI":"10.1007\/s11701-026-03775-x","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T01:33:41Z","timestamp":1785980021000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence-supported segmentation of cardiac anatomy in open-heart surgery videos"],"prefix":"10.1007","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5822-876X","authenticated-orcid":false,"given":"Maj","family":"Stenmark","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia","family":"\u00d6nerud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahriar","family":"Anvariazar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phan-Kiet","family":"Tran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,6]]},"reference":[{"issue":"7","key":"3775_CR1","doi-asserted-by":"publisher","first-page":"e198067","DOI":"10.1001\/jamanetworkopen.2019.8067","volume":"2","author":"JW Suliburk","year":"2019","unstructured":"Suliburk JW et al (2019) Analysis of Human Performance Deficiencies Associated With Surgical Adverse Events. 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