{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T11:39:51Z","timestamp":1759577991836,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031439926"},{"type":"electronic","value":"9783031439933"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-43993-3_31","type":"book-chapter","created":{"date-parts":[[2023,9,30]],"date-time":"2023-09-30T23:08:57Z","timestamp":1696115337000},"page":"318-327","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Vertex Correspondence in\u00a0Cortical Surface Reconstruction"],"prefix":"10.1007","author":[{"given":"Anne-Marie","family":"Rickmann","sequence":"first","affiliation":[]},{"given":"Fabian","family":"Bongratz","sequence":"additional","affiliation":[]},{"given":"Christian","family":"Wachinger","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,10,1]]},"reference":[{"key":"31_CR1","doi-asserted-by":"crossref","unstructured":"Desikan, R.S., et al.: An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31(3), 968\u2013980 (2006)","DOI":"10.1016\/j.neuroimage.2006.01.021"},{"key":"31_CR2","unstructured":"Hoopes, A., Greve, D.: TopoFit GitHub repository. https:\/\/github.com\/ahoopes\/topofit. Accessed 04 Mar 2023"},{"key":"31_CR3","doi-asserted-by":"crossref","unstructured":"Bongratz, F., Rickmann, A.M., P\u00f6lsterl, S., Wachinger, C.: Vox2Cortex: fast explicit reconstruction of cortical surfaces from 3D MRI scans with geometric deep neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 20773\u201320783 (2022)","DOI":"10.1109\/CVPR52688.2022.02011"},{"key":"31_CR4","doi-asserted-by":"crossref","unstructured":"Cruz, R.S., Lebrat, L., Bourgeat, P., Fookes, C., Fripp, J., Salvado, O.: DeepCSR: a 3D deep learning approach for cortical surface reconstruction. In: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 806\u2013815 (2021)","DOI":"10.1109\/WACV48630.2021.00085"},{"key":"31_CR5","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1016\/j.neuroimage.2012.09.050","volume":"65","author":"R Dahnke","year":"2013","unstructured":"Dahnke, R., Yotter, R.A., Gaser, C.: Cortical thickness and central surface estimation. Neuroimage 65, 336\u2013348 (2013)","journal-title":"Neuroimage"},{"key":"31_CR6","unstructured":"Bongratz, F., Bongratz, F., Rickmann, A. M.: Vox2Cortex github repository. https:\/\/github.com\/ai-med\/Vox2Cortex. Accessed 04 Mar 2023"},{"key":"31_CR7","doi-asserted-by":"crossref","unstructured":"Fischl, B., Sereno, M., Tootell, R., Dale, A.: High-resolution inter-subject averaging and a coordinate system for the cortical surface. Hum. Brain Mapp. 8(4), 272\u2013284 (1999).https:\/\/surfer.nmr.mgh.harvard.edu\/ftp\/articles\/fischl99-morphing.pdf","DOI":"10.1002\/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4"},{"issue":"2","key":"31_CR8","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.neuroimage.2012.01.021","volume":"62","author":"B Fischl","year":"2012","unstructured":"Fischl, B.: FreeSurfer. Neuroimage 62(2), 774\u2013781 (2012)","journal-title":"Neuroimage"},{"issue":"2","key":"31_CR9","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1006\/nimg.1998.0396","volume":"9","author":"B Fischl","year":"1999","unstructured":"Fischl, B., Sereno, M.I., Dale, A.M.: Cortical surface-based analysis: II: inflation, flattening, and a surface-based coordinate system. Neuroimage 9(2), 195\u2013207 (1999)","journal-title":"Neuroimage"},{"key":"31_CR10","doi-asserted-by":"publisher","first-page":"117012","DOI":"10.1016\/j.neuroimage.2020.117012","volume":"219","author":"L Henschel","year":"2020","unstructured":"Henschel, L., Conjeti, S., Estrada, S., Diers, K., Fischl, B., Reuter, M.: FastSurfer - a fast and accurate deep learning based neuroimaging pipeline. Neuroimage 219, 117012 (2020)","journal-title":"Neuroimage"},{"key":"31_CR11","unstructured":"Hoopes, A., Iglesias, J.E., Fischl, B., Greve, D., Dalca, A.V.: TopoFit: rapid reconstruction of topologically-correct cortical surfaces. In: Medical Imaging with Deep Learning (2021)"},{"key":"31_CR12","doi-asserted-by":"publisher","first-page":"171","DOI":"10.3389\/fnins.2012.00171","volume":"6","author":"A Klein","year":"2012","unstructured":"Klein, A., Tourville, J.: 101 labeled brain images and a consistent human cortical labeling protocol. Front. Neurosci. 6, 171 (2012). https:\/\/doi.org\/10.3389\/fnins.2012.00171","journal-title":"Front. Neurosci."},{"key":"31_CR13","unstructured":"Lebrat, L., et al.: CorticalFlow: a diffeomorphic mesh transformer network for cortical surface reconstruction. In: Advances in Neural Information Processing Systems, vol. 34 (2021)"},{"issue":"7","key":"31_CR14","doi-asserted-by":"publisher","first-page":"995","DOI":"10.1093\/cercor\/bhh200","volume":"15","author":"JP Lerch","year":"2005","unstructured":"Lerch, J.P., Pruessner, J.C., Zijdenbos, A.P., Hampel, H., Teipel, S.J., Evans, A.C.: Focal decline of cortical thickness in Alzheimer\u2019s disease identified by computational neuroanatomy. Cereb. Cortex 15(7), 995\u20131001 (2005)","journal-title":"Cereb. Cortex"},{"key":"31_CR15","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1109\/TMI.2022.3206221","volume":"42","author":"Q Ma","year":"2022","unstructured":"Ma, Q., Li, L., Robinson, E.C., Kainz, B., Rueckert, D., Alansary, A.: CortexODE: learning cortical surface reconstruction by neural odes. IEEE Trans. Med. Imaging 42, 430\u2013443 (2022)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"31_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2014.37","volume":"1","author":"JR Maclaren","year":"2014","unstructured":"Maclaren, J.R., Han, Z., Vos, S.B., Fischbein, N.J., Bammer, R.: Reliability of brain volume measurements: a test-retest dataset. Sci. Data 1, 1\u20139 (2014)","journal-title":"Sci. Data"},{"issue":"1","key":"31_CR17","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1038\/s41467-021-21057-y","volume":"12","author":"JM Roe","year":"2021","unstructured":"Roe, J.M., et al.: Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer\u2019s disease. Nat. Commun. 12(1), 721 (2021)","journal-title":"Nat. Commun."},{"key":"31_CR18","unstructured":"Santa Cruz, R., et al.: CorticalFlow++. https:\/\/bitbucket.csiro.au\/projects\/CRCPMAX\/repos\/corticalflow\/browse. Accessed 04 Mar 2023"},{"key":"31_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1007\/978-3-031-16443-9_48","volume-title":"Medical Image Computing and Computer Assisted Intervention - MICCAI 2022","author":"R Santa Cruz","year":"2022","unstructured":"Santa Cruz, R., et al.: CorticalFlow++: boosting cortical surface reconstruction accuracy, regularity, and interoperability. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13435, pp. 496\u2013505. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16443-9_48"},{"key":"31_CR20","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.neurobiolaging.2015.12.009","volume":"39","author":"ME Shaw","year":"2016","unstructured":"Shaw, M.E., Sachdev, P.S., Anstey, K.J., Cherbuin, N.: Age-related cortical thinning in cognitively healthy individuals in their 60s: the path through life study. Neurobiol. Aging 39, 202\u2013209 (2016). https:\/\/doi.org\/10.1016\/j.neurobiolaging.2015.12.009","journal-title":"Neurobiol. Aging"},{"issue":"11","key":"31_CR21","doi-asserted-by":"publisher","first-page":"2885","DOI":"10.1093\/brain\/awl256","volume":"129","author":"V Singh","year":"2006","unstructured":"Singh, V., Chertkow, H., Lerch, J.P., Evans, A.C., Dorr, A.E., Kabani, N.J.: Spatial patterns of cortical thinning in mild cognitive impairment and Alzheimer\u2019s disease. Brain 129(11), 2885\u20132893 (2006)","journal-title":"Brain"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-43993-3_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T16:09:19Z","timestamp":1712074159000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43993-3_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031439926","9783031439933"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43993-3_31","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"1 October 2023","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":"Vancouver, BC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2023\/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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2250","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":"730","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":"32% - 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":"5","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)"}}]}}