{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T13:56:01Z","timestamp":1758981361710,"version":"3.44.0"},"publisher-location":"Singapore","reference-count":15,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819638628"},{"type":"electronic","value":"9789819638635"}],"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\/978-981-96-3863-5_52","type":"book-chapter","created":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T03:40:56Z","timestamp":1743824456000},"page":"569-578","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Learning Wall Segmentation in\u00a03D Vessel Trees Using Sparse Annotations"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-1870-9290","authenticated-orcid":false,"given":"Hinrich","family":"Rahlfs","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4948-0917","authenticated-orcid":false,"given":"Markus","family":"H\u00fcllebrand","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4410-6790","authenticated-orcid":false,"given":"Sebastian","family":"Schmitter","sequence":"additional","affiliation":[]},{"given":"Christoph","family":"Strecker","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3252-7910","authenticated-orcid":false,"given":"Andreas","family":"Harloff","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0737-7375","authenticated-orcid":false,"given":"Anja","family":"Hennemuth","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,4]]},"reference":[{"issue":"1","key":"52_CR1","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1038\/s41572-019-0118-8","volume":"5","author":"BC Campbell","year":"2019","unstructured":"Campbell, B.C., De Silva, D.A., Macleod, M.R., Coutts, S.B., Schwamm, L.H., Davis, S.M., Donnan, G.A.: Ischaemic stroke. Nat. Rev. Dis. Primers 5(1), 70 (2019)","journal-title":"Nat. Rev. Dis. Primers"},{"issue":"8","key":"52_CR2","doi-asserted-by":"publisher","first-page":"1621","DOI":"10.3174\/ajnr.A3028","volume":"33","author":"R Van\u2019t Klooster","year":"2012","unstructured":"Van\u2019t Klooster, R., et al.: Automated versus manual in vivo segmentation of carotid plaque MRI. Am. J. Neuroradiol. 33(8), 1621\u20131627 (2012)","journal-title":"Am. J. Neuroradiol."},{"issue":"4","key":"52_CR3","doi-asserted-by":"publisher","first-page":"045033","DOI":"10.1088\/1361-6560\/abd4bb","volume":"66","author":"C Zhu","year":"2021","unstructured":"Zhu, C., et al.: Cascaded residual U-net for fully automatic segmentation of 3D carotid artery in high-resolution multi-contrast MR images. Phys. Med. Biol. 66(4), 045033 (2021)","journal-title":"Phys. Med. Biol."},{"key":"52_CR4","doi-asserted-by":"publisher","first-page":"26637","DOI":"10.1109\/ACCESS.2023.3258408","volume":"11","author":"E Lavrova","year":"2023","unstructured":"Lavrova, E., et al.: UR-CarA-Net: a cascaded framework with uncertainty regularization for automated segmentation of carotid arteries on black blood MR images. IEEE Access 11, 26637\u201326651 (2023)","journal-title":"IEEE Access"},{"key":"52_CR5","unstructured":"Hu, S., Liao, Z., Xia, Y.: Label propagation for 3D carotid vessel wall segmentation and atherosclerosis diagnosis. arXiv preprint arXiv:2208.13337 (2022)"},{"issue":"4","key":"52_CR6","doi-asserted-by":"publisher","first-page":"044504","DOI":"10.1117\/1.JMI.11.4.044504","volume":"11","author":"J Brosig","year":"2024","unstructured":"Brosig, J., et al.: Learning three-dimensional aortic root assessment based on sparse annotations. In J. Med. Imag. 11(4), 044504 (2024). https:\/\/doi.org\/10.1117\/1.JMI.11.4.044504","journal-title":"In J. Med. Imag."},{"key":"52_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12968-020-00657-5","volume":"22","author":"C Strecker","year":"2020","unstructured":"Strecker, C., et al.: Carotid geometry is an independent predictor of wall thickness-a 3D cardiovascular magnetic resonance study in patients with high cardiovascular risk. J. Cardiovasc. Magn. Reson. 22, 1\u201312 (2020)","journal-title":"J. Cardiovasc. Magn. Reson."},{"key":"52_CR8","doi-asserted-by":"publisher","first-page":"723860","DOI":"10.3389\/fcvm.2021.723860","volume":"8","author":"C Strecker","year":"2021","unstructured":"Strecker, C., et al.: Carotid geometry and wall shear stress independently predict increased wall thickness\u2013a longitudinal 3D MRI study in high-risk patients. Front. Cardiovasc. Med. 8, 723860 (2021)","journal-title":"Front. Cardiovasc. Med."},{"key":"52_CR9","doi-asserted-by":"publisher","unstructured":"Blausen.com staff. Medical gallery of Blausen Medical 2014. WikiJ. Med. 1(2) (2014). https:\/\/doi.org\/10.15347\/wjm\/2014.010. ISSN 2002-4436","DOI":"10.15347\/wjm\/2014.010"},{"issue":"4","key":"52_CR10","doi-asserted-by":"publisher","first-page":"044503","DOI":"10.1117\/1.JMI.11.4.044503","volume":"11","author":"H Rahlfs","year":"2024","unstructured":"Rahlfs, H., H\u00fcllebrand, M., Schmitter, S., Strecker, C., Harloff, A., Hennemuth, A.: Learning carotid vessel wall segmentation in black blood MRI using sparsely sampled cross-sections from 3D data. In J. Med. Imag. 11(4), 044503 (2024). https:\/\/doi.org\/10.1117\/1.JMI.11.4.044503","journal-title":"In J. Med. Imag."},{"issue":"3","key":"52_CR11","doi-asserted-by":"publisher","first-page":"916","DOI":"10.1161\/STROKEAHA.111.636084","volume":"43","author":"GM von Reutern","year":"2012","unstructured":"von Reutern, G.M., et al.: Grading carotid stenosis using ultrasonic methods. Stroke 43(3), 916\u2013921 (2012)","journal-title":"Stroke"},{"key":"52_CR12","unstructured":"Yuan, C., et al.: Carotid artery vessel wall segmentation challenge. https:\/\/vessel-wall-segmentation.grandchallenge.org\/. Accessed 22 July 2024)"},{"key":"52_CR13","unstructured":"Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of the Fourth Eurographics Symposium on Geometry Processing, vol. 7, no. 4 (2006)"},{"issue":"2","key":"52_CR14","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":"2","key":"52_CR15","doi-asserted-by":"publisher","first-page":"E9","DOI":"10.3174\/ajnr.A5488","volume":"39","author":"L Saba","year":"2018","unstructured":"Saba, L., et al.: Carotid artery wall imaging: perspective and guidelines from the ASNR vessel wall imaging study group and expert consensus recommendations of the American society of neuroradiology. Am. J. Neuroradiol. 39(2), E9\u2013E31 (2018)","journal-title":"Am. J. Neuroradiol."}],"container-title":["Lecture Notes in Electrical Engineering","Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-3863-5_52","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T09:38:26Z","timestamp":1757151506000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-3863-5_52"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819638628","9789819638635"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-3863-5_52","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"type":"print","value":"1876-1100"},{"type":"electronic","value":"1876-1119"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"4 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MICAD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Imaging and Computer-Aided Diagnosis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Manchester","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 November 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 November 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"micad2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.micad.org\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}