{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T08:38:17Z","timestamp":1769848697214,"version":"3.49.0"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030597245","type":"print"},{"value":"9783030597252","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-59725-2_13","type":"book-chapter","created":{"date-parts":[[2020,10,2]],"date-time":"2020-10-02T15:02:49Z","timestamp":1601650969000},"page":"128-137","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Vascular Surface Segmentation for Intracranial Aneurysm Isolation and Quantification"],"prefix":"10.1007","author":[{"given":"\u017diga","family":"Bizjak","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo\u0161tjan","family":"Likar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Franjo","family":"Pernu\u0161","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u017diga","family":"\u0160piclin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,29]]},"reference":[{"issue":"5","key":"13_CR1","doi-asserted-by":"publisher","first-page":"722","DOI":"10.1227\/00006123-198905000-00011","volume":"24","author":"GM Austin","year":"1989","unstructured":"Austin, G.M., Austin, G.M., Schievink, W., Williams, R.: Controlled pressure-volume factors in the enlargement of intracranial aneurysms. Neurosurgery 24(5), 722\u2013730 (1989)","journal-title":"Neurosurgery"},{"key":"13_CR2","doi-asserted-by":"publisher","unstructured":"Backes, D., et al.: ELAPSS score for prediction of risk of growth of unruptured intracranial aneurysms 88(17), 1600\u20131606 (2017). https:\/\/doi.org\/10.1212\/WNL.0000000000003865, http:\/\/europepmc.org\/abstract\/med\/28363976","DOI":"10.1212\/WNL.0000000000003865"},{"key":"13_CR3","doi-asserted-by":"publisher","unstructured":"Brinjikji, W., et al.: Risk factors for growth of intracranial aneurysms: a systematic review and meta-analysis 37(4), 615\u2013620 (2016). https:\/\/doi.org\/10.3174\/ajnr.A4575, http:\/\/www.ajnr.org\/content\/37\/4\/615","DOI":"10.3174\/ajnr.A4575"},{"key":"13_CR4","doi-asserted-by":"publisher","unstructured":"Brown, R.D., Broderick, J.P.: Unruptured intracranial aneurysms: epidemiology, natural history, management options, and familial screening 13(4), 393\u2013404 (2014). https:\/\/doi.org\/10.1016\/S1474-4422(14)70015-8, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1474442214700158","DOI":"10.1016\/S1474-4422(14)70015-8"},{"issue":"3","key":"13_CR5","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1007\/s11517-012-1003-8","volume":"51","author":"R C\u00e1rdenes","year":"2013","unstructured":"C\u00e1rdenes, R., Larrabide, I., San Rom\u00e1n, L., Frangi, A.F.: Performance assessment of isolation methods for geometrical cerebral aneurysm analysis. Med. Biol. Eng. Comput. 51(3), 343\u2013352 (2013)","journal-title":"Med. Biol. Eng. Comput."},{"issue":"10","key":"13_CR6","doi-asserted-by":"publisher","first-page":"1863","DOI":"10.1109\/TMI.2011.2157698","volume":"30","author":"R C\u00e1rdenes","year":"2011","unstructured":"C\u00e1rdenes, R., Pozo, J.M., Bogunovic, H., Larrabide, I., Frangi, A.F.: Automatic aneurysm neck detection using surface voronoi diagrams. IEEE Trans. Med. Imaging 30(10), 1863\u20131876 (2011)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"8","key":"13_CR7","doi-asserted-by":"publisher","first-page":"985","DOI":"10.1002\/nme.205","volume":"51","author":"JR Cebral","year":"2001","unstructured":"Cebral, J.R., L\u00f6hner, R.: From medical images to anatomically accurate finite element grids. Int. J. Numeric. Methods Eng. 51(8), 985\u20131008 (2001)","journal-title":"Int. J. Numeric. Methods Eng."},{"key":"13_CR8","doi-asserted-by":"publisher","unstructured":"Chien, A., et al.: Unruptured intracranial aneurysm growth trajectory: occurrence and rate of enlargement in 520 longitudinally followed cases 1, 1\u201311 (2019). https:\/\/doi.org\/10.3171\/2018.11.JNS181814, https:\/\/thejns.org\/view\/journals\/j-neurosurg\/aop\/article-10.3171-2018.11.JNS181814.xml","DOI":"10.3171\/2018.11.JNS181814"},{"issue":"1","key":"13_CR9","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1186\/s12938-019-0726-2","volume":"18","author":"H Duan","year":"2019","unstructured":"Duan, H., Huang, Y., Liu, L., Dai, H., Chen, L., Zhou, L.: Automatic detection on intracranial aneurysm from digital subtraction angiography with cascade convolutional neural networks. Biomed. Eng. Online 18(1), 110 (2019)","journal-title":"Biomed. Eng. Online"},{"key":"13_CR10","doi-asserted-by":"publisher","unstructured":"Ishibashi, T., et al.: Unruptured intracranial aneurysms 40(1), 313\u2013316 (2009). https:\/\/doi.org\/10.1161\/STROKEAHA.108.521674, https:\/\/doi.org\/10.1161\/STROKEAHA.108.521674","DOI":"10.1161\/STROKEAHA.108.521674"},{"issue":"2","key":"13_CR11","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/TBME.2019.2918921","volume":"67","author":"T Jerman","year":"2019","unstructured":"Jerman, T., Chien, A., Pernus, F., Likar, B., Spiclin, Z.: Automated cutting plane positioning for intracranial aneurysm quantification. IEEE Trans. Biomed. Eng. 67(2), 577\u2013587 (2019)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Jerman, T., Pernus, F., Likar, B., \u0160piclin, \u017d.: Aneurysm detection in 3d cerebral angiograms based on intra-vascular distance mapping and convolutional neural networks. In: 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 612\u2013615. IEEE (2017)","DOI":"10.1109\/ISBI.2017.7950595"},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Jin, H., Yin, Y., Hu, M., Yang, G., Qin, L.: Fully automated unruptured intracranial aneurysm detection and segmentation from digital subtraction angiography series using an end-to-end spatiotemporal deep neural network. In: Medical Imaging 2019: Image Processing, vol. 10949, p. 109491I. International Society for Optics and Photonics (2019)","DOI":"10.1117\/12.2512623"},{"issue":"4","key":"13_CR14","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1227\/01.NEU.0000156790.28794.EA","volume":"56","author":"Y Kai","year":"2005","unstructured":"Kai, Y., Hamada, J.I., Morioka, M., Yano, S., Kuratsu, J.I.: Evaluation of the stability of small ruptured aneurysms with a small neck after embolization with guglielmi detachable coils: correlation between coil packing ratio and coil compaction. Neurosurgery 56(4), 785\u2013792 (2005)","journal-title":"Neurosurgery"},{"issue":"5","key":"13_CR15","doi-asserted-by":"publisher","first-page":"2439","DOI":"10.1118\/1.3575417","volume":"38","author":"I Larrabide","year":"2011","unstructured":"Larrabide, I., et al.: Three-dimensional morphological analysis of intracranial aneurysms: a fully automated method for aneurysm sac isolation and quantification. Med. Phys. 38(5), 2439\u20132449 (2011)","journal-title":"Med. Phys."},{"key":"13_CR16","doi-asserted-by":"crossref","unstructured":"Lawonn, K., Meuschke, M., Wickenh\u00f6fer, R., Preim, B., Hildebrandt, K.: A geometric optimization approach for the detection and segmentation of multiple aneurysms. In: Computer Graphics Forum, vol. 38, pp. 413\u2013425. Wiley Online Library (2019)","DOI":"10.1111\/cgf.13699"},{"issue":"2","key":"13_CR17","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1023\/B:ABME.0000012746.31343.92","volume":"32","author":"B Ma","year":"2004","unstructured":"Ma, B., Harbaugh, R.E., Raghavan, M.L.: Three-dimensional geometrical characterization of cerebral aneurysms. Ann. Biomed. Eng. 32(2), 264\u2013273 (2004)","journal-title":"Ann. Biomed. Eng."},{"issue":"10","key":"13_CR18","doi-asserted-by":"publisher","first-page":"2188","DOI":"10.1007\/s10439-012-0577-5","volume":"40","author":"M Piccinelli","year":"2012","unstructured":"Piccinelli, M., Steinman, D.A., Hoi, Y., Tong, F., Veneziani, A., Antiga, L.: Automatic neck plane detection and 3D geometric characterization of aneurysmal sacs. Ann. Biomed. Eng. 40(10), 2188\u20132211 (2012)","journal-title":"Ann. Biomed. Eng."},{"key":"13_CR19","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: Pointnet: deep learning on point sets for 3D classification and segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 652\u2013660 (2017)"},{"issue":"11","key":"13_CR20","doi-asserted-by":"publisher","first-page":"1781","DOI":"10.1007\/s11548-018-1848-x","volume":"13","author":"S Saalfeld","year":"2018","unstructured":"Saalfeld, S., Berg, P., Niemann, A., Luz, M., Preim, B., Beuing, O.: Semiautomatic neck curve reconstruction for intracranial aneurysm rupture risk assessment based on morphological parameters. Int. J. Comput. Assist. Radiol. Surg. 13(11), 1781\u20131793 (2018). https:\/\/doi.org\/10.1007\/s11548-018-1848-x","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"issue":"12","key":"13_CR21","doi-asserted-by":"publisher","first-page":"942","DOI":"10.1007\/s00234-005-1446-9","volume":"47","author":"MJ Slob","year":"2005","unstructured":"Slob, M.J., Sluzewski, M., van Rooij, W.J.: The relation between packing and reopening in coiled intracranial aneurysms: a prospective study. Neuroradiology 47(12), 942\u2013945 (2005)","journal-title":"Neuroradiology"},{"issue":"3","key":"13_CR22","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.medengphy.2007.04.011","volume":"30","author":"A Valencia","year":"2008","unstructured":"Valencia, A., Morales, H., Rivera, R., Bravo, E., Galvez, M.: Blood flow dynamics in patient-specific cerebral aneurysm models: the relationship between wall shear stress and aneurysm area index. Med. Eng. Phys. 30(3), 329\u2013340 (2008)","journal-title":"Med. Eng. Phys."},{"key":"13_CR23","doi-asserted-by":"publisher","unstructured":"Wiebers, D.O.: Unruptured intracranial aneurysms: natural history, clinical outcome, and risks of surgical and endovascular treatment 362(9378), 103\u2013110 (2003). https:\/\/doi.org\/10.1016\/S0140-6736(03)13860-3, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0140673603138603","DOI":"10.1016\/S0140-6736(03)13860-3"},{"key":"13_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/978-3-030-32251-9_27","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019","author":"M Zhou","year":"2019","unstructured":"Zhou, M., Wang, X., Wu, Z., Pozo, J.M., Frangi, A.F.: Intracranial aneurysm detection from 3D vascular mesh models with ensemble deep learning. In: Shen, D., et al. (eds.) MICCAI 2019. LNCS, vol. 11767, pp. 243\u2013252. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32251-9_27"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59725-2_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T22:07:12Z","timestamp":1759356432000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59725-2_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030597245","9783030597252"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59725-2_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"29 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lima","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Peru","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2020","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":"miccai2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.miccai2020.org\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1809","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"542","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}