{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T06:43:20Z","timestamp":1774680200302,"version":"3.50.1"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031959172","type":"print"},{"value":"9783031959189","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-95918-9_16","type":"book-chapter","created":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T13:30:27Z","timestamp":1750512627000},"page":"227-239","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Active Learning with\u00a0nnUNet for\u00a0Coronary Artery Lumen Segmentation Using a\u00a0Centerline Prior"],"prefix":"10.1007","author":[{"given":"Anna B\u00f8gevang","family":"Ekner","sequence":"first","affiliation":[]},{"given":"Mathias Micheelsen","family":"Lowes","sequence":"additional","affiliation":[]},{"given":"Rasmus R.","family":"Paulsen","sequence":"additional","affiliation":[]},{"given":"Klaus Fuglsang","family":"Kofoed","sequence":"additional","affiliation":[]},{"given":"Andreas Ohrt","family":"Johansen","sequence":"additional","affiliation":[]},{"given":"Kristine Aavild","family":"S\u00f8rensen","sequence":"additional","affiliation":[]},{"given":"Josefine Vilsb\u00f8ll","family":"Sundgaard","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,16]]},"reference":[{"issue":"7","key":"16_CR1","doi-asserted-by":"publisher","first-page":"e015539","DOI":"10.1161\/JAHA.119.015539","volume":"9","author":"HA DeVon","year":"2020","unstructured":"DeVon, H.A., Mirzaei, S., Z\u00e8gre-Hemsey, J.: Typical and atypical symptoms of acute coronary syndrome: time to retire the terms? J. Am. Heart Assoc. 9(7), e015539 (2020). https:\/\/doi.org\/10.1161\/JAHA.119.015539","journal-title":"J. Am. Heart Assoc."},{"key":"16_CR2","doi-asserted-by":"crossref","unstructured":"Dodge\u00a0Jr., J.T., Brown, B.G., Bolson, E.L., Dodge, H.T.: Lumen diameter of normal human coronary arteries. Influence of age, sex, anatomic variation, and left ventricular hypertrophy or dilation. Circulation 86(1), 232\u2013246 (1992)","DOI":"10.1161\/01.CIR.86.1.232"},{"key":"16_CR3","unstructured":"F\u00f6llmer, B., Schulze, K., Wald, C., Stober, S., Samek, W., Dewey, M.: Active learning with the nnUNet and sample selection with uncertainty-aware submodular mutual information measure. In: Medical Imaging with Deep Learning (2024)"},{"key":"16_CR4","doi-asserted-by":"publisher","unstructured":"Ghekiere, O., et al.: Image quality in coronary CT angiography: challenges and technical solutions. Br. J. Radiol. 90(1072) (2017). https:\/\/doi.org\/10.1259\/bjr.20160567","DOI":"10.1259\/bjr.20160567"},{"issue":"2","key":"16_CR5","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., Petersen, J., Maier-Hein, K.H.: nnU-net: a self-configuring method for deep learning-based biomedical image segmentation. Nat. Methods 18(2), 203\u2013211 (2021)","journal-title":"Nat. Methods"},{"issue":"25","key":"16_CR6","doi-asserted-by":"publisher","first-page":"745","DOI":"10.21105\/joss.00745","volume":"3","author":"R Izzo","year":"2018","unstructured":"Izzo, R., Steinman, D., Manini, S., Antiga, L.: The vascular modeling toolkit: a python library for the analysis of tubular structures in medical images. J. Open Sour. Softw. 3(25), 745 (2018)","journal-title":"J. Open Sour. Softw."},{"key":"16_CR7","doi-asserted-by":"crossref","unstructured":"Ji, Y., Kaestner, D., Wirth, O., Wressnegger, C.: Randomness is the root of all evil: more reliable evaluation of deep active learning. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 3943\u20133952 (2023)","DOI":"10.1109\/WACV56688.2023.00393"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Munjal, P., Hayat, N., Hayat, M., Sourati, J., Khan, S.: Towards robust and reproducible active learning using neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 223\u2013232 (2022)","DOI":"10.1109\/CVPR52688.2022.00032"},{"key":"16_CR9","unstructured":"Ren, P., et al.: A survey of deep active learning. arXiv preprint arXiv:2009.00236 (2020)"},{"issue":"5","key":"16_CR10","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1016\/j.media.2009.06.003","volume":"13","author":"M Schaap","year":"2009","unstructured":"Schaap, M., et al.: Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms. Med. Image Anal. 13(5), 701\u2013714 (2009)","journal-title":"Med. Image Anal."},{"issue":"1","key":"16_CR11","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1145\/584091.584093","volume":"5","author":"CE Shannon","year":"2001","unstructured":"Shannon, C.E.: A mathematical theory of communication. ACM SIGMOBILE Mob. Comput. Commun. Rev. 5(1), 3\u201355 (2001)","journal-title":"ACM SIGMOBILE Mob. Comput. Commun. Rev."},{"key":"16_CR12","doi-asserted-by":"publisher","unstructured":"Theofilis, P., et al.: Silent myocardial ischemia: from pathophysiology to diagnosis and treatment. Biomedicines 12(2) (2024). https:\/\/doi.org\/10.3390\/biomedicines12020259","DOI":"10.3390\/biomedicines12020259"},{"issue":"36","key":"16_CR13","doi-asserted-by":"publisher","first-page":"3415","DOI":"10.1093\/eurheartj\/ehae177","volume":"45","author":"C Vrints","year":"2024","unstructured":"Vrints, C., et al.: 2024 esc guidelines for the management of chronic coronary syndromes: developed by the task force for the management of chronic coronary syndromes of the European society of cardiology (ESC) endorsed by the European association for cardio-thoracic surgery (EACTS). Eur. Heart J. 45(36), 3415\u20133537 (2024)","journal-title":"Eur. Heart J."},{"issue":"12","key":"16_CR14","doi-asserted-by":"publisher","first-page":"2591","DOI":"10.1109\/TCSVT.2016.2589879","volume":"27","author":"K Wang","year":"2016","unstructured":"Wang, K., Zhang, D., Li, Y., Zhang, R., Lin, L.: Cost-effective active learning for deep image classification. IEEE Trans. Circuits Syst. Video Technol. 27(12), 2591\u20132600 (2016)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"16_CR15","doi-asserted-by":"crossref","unstructured":"Wasserthal, J., et\u00a0al.: Totalsegmentator: robust segmentation of 104 anatomic structures in CT images. Radiol.: Artif. Intell. 5(5) (2023)","DOI":"10.1148\/ryai.230024"},{"key":"16_CR16","unstructured":"Weber, C., Brown, K.N., Borger, J.: Anatomy, Thorax, Heart Anomalous Left Anterior Descending (LAD) Artery. StatPearls Publishing (2019)"},{"key":"16_CR17","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.media.2018.10.005","volume":"51","author":"JM Wolterink","year":"2019","unstructured":"Wolterink, J.M., van Hamersvelt, R.W., Viergever, M.A., Leiner, T., I\u0161gum, I.: Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier. Med. Image Anal. 51, 46\u201360 (2019)","journal-title":"Med. Image Anal."},{"key":"16_CR18","unstructured":"World Health Organization: Cardiovascular diseases (CVDs). https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/cardiovascular-diseases-(cvds). Accessed 09 Dec 2024"},{"issue":"2","key":"16_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3379504","volume":"53","author":"J Wu","year":"2020","unstructured":"Wu, J., et al.: Multi-label active learning algorithms for image classification: overview and future promise. ACM Comput. Surv. (CSUR) 53(2), 1\u201335 (2020)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"16_CR20","doi-asserted-by":"crossref","unstructured":"Wu, J., Chen, J., Huang, D.: Entropy-based active learning for object detection with progressive diversity constraint. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9397\u20139406 (2022)","DOI":"10.1109\/CVPR52688.2022.00918"},{"key":"16_CR21","doi-asserted-by":"crossref","unstructured":"Yang, L., Zhang, Y., Chen, J., Zhang, S., Chen, D.Z.: Suggestive annotation: a deep active learning framework for biomedical image segmentation. In: Medical Image Computing and Computer Assisted Intervention- MICCAI 2017: 20th International Conference, Quebec City, QC, Canada, 11\u201313 September 2017, Proceedings, Part III 20, pp. 399\u2013407. Springer (2017)","DOI":"10.1007\/978-3-319-66179-7_46"},{"key":"16_CR22","doi-asserted-by":"crossref","unstructured":"Yang, Y., Tannenbaum, A., Giddens, D., Stillman, A.: Automatic segmentation of coronary arteries using Bayesian driven implicit surfaces. In: 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 189\u2013192. IEEE (2007)","DOI":"10.1109\/ISBI.2007.356820"},{"key":"16_CR23","doi-asserted-by":"publisher","first-page":"102287","DOI":"10.1016\/j.compmedimag.2023.102287","volume":"109","author":"A Zeng","year":"2023","unstructured":"Zeng, A., et al.: ImageCAS: a large-scale dataset and benchmark for coronary artery segmentation based on computed tomography angiography images. Comput. Med. Imaging Graph. 109, 102287 (2023)","journal-title":"Comput. Med. Imaging Graph."},{"key":"16_CR24","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Yang, X., Veeravalli, B., Zeng, Z.: Deeply supervised active learning for finger bones segmentation. In: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 1620\u20131623. IEEE (2020)","DOI":"10.1109\/EMBC44109.2020.9176662"}],"container-title":["Lecture Notes in Computer Science","Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-95918-9_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T05:17:52Z","timestamp":1774675072000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-95918-9_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031959172","9783031959189"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-95918-9_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"16 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SCIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Scandinavian Conference on Image Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Reykjavik","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Iceland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"scia2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/scia2025.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}