{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T08:51:02Z","timestamp":1775983862140,"version":"3.50.1"},"publisher-location":"Cham","reference-count":46,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031734793","type":"print"},{"value":"9783031734809","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-73480-9_25","type":"book-chapter","created":{"date-parts":[[2024,10,4]],"date-time":"2024-10-04T08:02:10Z","timestamp":1728028930000},"page":"321-332","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["High Performance Groupwise Cortical Surface Registration with\u00a0Multimodal Surface Matching"],"prefix":"10.1007","author":[{"given":"Renato","family":"Besenczi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yourong","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emma C.","family":"Robinson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,5]]},"reference":[{"key":"25_CR1","doi-asserted-by":"crossref","unstructured":"Ahmad, S., et\u00a0al.: Deep learning deformation initialization for rapid groupwise registration of inhomogeneous image populations. Frontiers in Neuroinformatics 13(May), 1\u201312 (2019)","DOI":"10.3389\/fninf.2019.00034"},{"key":"25_CR2","doi-asserted-by":"crossref","unstructured":"Amunts, K., et\u00a0al.: Brodmann\u2019s areas 17 and 18 brought into stereotaxic space-where and how variable? Neuroimage 11(1), 66\u201384 (2000)","DOI":"10.1006\/nimg.1999.0516"},{"key":"25_CR3","doi-asserted-by":"crossref","unstructured":"Ball, G., et\u00a0al.: Molecular signatures of cortical expansion in the human fetal brain. bioRxiv pp. 2024\u201302 (2024)","DOI":"10.1101\/2024.02.13.580198"},{"key":"25_CR4","doi-asserted-by":"crossref","unstructured":"Bhatia, K.K., et\u00a0al.: Consistent groupwise non-rigid registration for atlas construction. In: 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821). pp. 908\u2013911 Vol. 1. IEEE (2004)","DOI":"10.1109\/ISBI.2004.1398686"},{"key":"25_CR5","doi-asserted-by":"crossref","unstructured":"Dimitrova, R., et\u00a0al.: Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age. NeuroImage 243, 118488 (2021)","DOI":"10.1016\/j.neuroimage.2021.118488"},{"key":"25_CR6","doi-asserted-by":"crossref","unstructured":"Dong, P., et\u00a0al.: Efficient groupwise registration of MR brain images via hierarchical graph set shrinkage. Med. Image Comput. Comput. Assist. Interv. 11070, 819\u2013826 (Sep 2018)","DOI":"10.1007\/978-3-030-00928-1_92"},{"key":"25_CR7","doi-asserted-by":"crossref","unstructured":"Duan, D., et\u00a0al.: Exploring folding patterns of infant cerebral cortex based on multi-view curvature features: Methods and applications. Neuroimage 185, 575\u2013592 (2019)","DOI":"10.1016\/j.neuroimage.2018.08.041"},{"key":"25_CR8","doi-asserted-by":"crossref","unstructured":"Elliott, L.T., et\u00a0al.: Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature 562(7726), 210\u2013216 (2018)","DOI":"10.1038\/s41586-018-0571-7"},{"key":"25_CR9","unstructured":"Elseberg, J., et\u00a0al.: Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration. Journal of Software Engineering for Robotics 3(1), 2\u201312 (2012)"},{"key":"25_CR10","doi-asserted-by":"crossref","unstructured":"Fischl, B., et\u00a0al.: High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum. Brain Mapp. 8(4), 272\u2013284 (1999)","DOI":"10.1002\/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4"},{"key":"25_CR11","doi-asserted-by":"crossref","unstructured":"Fischl, B., et\u00a0al.: Cortical folding patterns and predicting cytoarchitecture. Cereb. Cortex 18(8), 1973\u20131980 (2008)","DOI":"10.1093\/cercor\/bhm225"},{"key":"25_CR12","doi-asserted-by":"crossref","unstructured":"Garrison, J.R., et\u00a0al.: Paracingulate sulcus morphology is associated with hallucinations in the human brain. Nature communications 6(1), \u00a08956 (2015)","DOI":"10.1038\/ncomms9956"},{"key":"25_CR13","doi-asserted-by":"crossref","unstructured":"Glasser, M.F., et\u00a0al.: The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage 80, 105\u2013124 (2013)","DOI":"10.1016\/j.neuroimage.2013.04.127"},{"key":"25_CR14","doi-asserted-by":"crossref","unstructured":"Glasser, M.F., et\u00a0al.: A multi-modal parcellation of human cerebral cortex. Nature 536(7615), 171\u2013178 (2016)","DOI":"10.1038\/nature18933"},{"key":"25_CR15","doi-asserted-by":"crossref","unstructured":"Gordon, E.M., et\u00a0al.: Generation and evaluation of a cortical area parcellation from resting-state correlations. Cerebral cortex 26(1), 288\u2013303 (2016)","DOI":"10.1093\/cercor\/bhu239"},{"key":"25_CR16","doi-asserted-by":"crossref","unstructured":"Guillon, L., et\u00a0al.: Identification of rare cortical folding patterns using unsupervised deep learning. Imaging Neuroscience 2, 1\u201327 (2024)","DOI":"10.1162\/imag_a_00084"},{"key":"25_CR17","unstructured":"Guo, Y., Suliman, M.A., Williams, L., Glasser, M.F., O\u2019Muircheartaigh, J., Robinson, E.: Uncovering common variants of cortical folding through hierarchical surface registration. OHBM (2023)"},{"key":"25_CR18","unstructured":"Guo, Y., Williams, L., Glasser, M.F., Suliman, M.A., Hammers, A., Van\u00a0Essen, D.C., O\u2019Muircheartaigh, J., Robinson, E.: Uncovering the asymmetry of common temporal lobe folding variants. OHBM (2024)"},{"key":"25_CR19","doi-asserted-by":"crossref","unstructured":"Haxby, J.V., et\u00a0al.: Hyperalignment: Modeling shared information encoded in idiosyncratic cortical topographies. Elife 9 (Jun 2020)","DOI":"10.7554\/eLife.56601"},{"key":"25_CR20","doi-asserted-by":"crossref","unstructured":"Heckemann, R.A., et\u00a0al.: Automatic anatomical brain MRI segmentation combining label propagation and decision fusion. NeuroImage 33(1), 115\u2013126 (2006)","DOI":"10.1016\/j.neuroimage.2006.05.061"},{"key":"25_CR21","doi-asserted-by":"crossref","unstructured":"Ishikawa, H.: Higher-order clique reduction without auxiliary variables. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 1362\u20131369 (2014)","DOI":"10.1109\/CVPR.2014.177"},{"key":"25_CR22","doi-asserted-by":"crossref","unstructured":"Jia, H., et\u00a0al.: Absorb: Atlas building by self-organized registration and bundling. NeuroImage 51(3), 1057\u20131070 (2010)","DOI":"10.1016\/j.neuroimage.2010.03.010"},{"key":"25_CR23","doi-asserted-by":"crossref","unstructured":"Joshi, S., et\u00a0al.: Unbiased diffeomorphic atlas construction for computational anatomy. NeuroImage 23, S151\u2013S160 (2004)","DOI":"10.1016\/j.neuroimage.2004.07.068"},{"key":"25_CR24","doi-asserted-by":"crossref","unstructured":"Komodakis, N., et\u00a0al.: Fast, approximately optimal solutions for single and dynamic MRFs. In: 2007 IEEE Conference on Computer Vision and Pattern Recognition. pp.\u00a01\u20138. IEEE (2007)","DOI":"10.1109\/CVPR.2007.383095"},{"key":"25_CR25","unstructured":"Kong, X.Z., et\u00a0al.: Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium. Proceedings of the National Academy of Sciences 115(22), E5154\u2013E5163 (2018)"},{"key":"25_CR26","unstructured":"Langs, G., et\u00a0al.: Functional geometry alignment and localization of brain areas. Advances in neural information processing systems 23 (2010)"},{"key":"25_CR27","doi-asserted-by":"crossref","unstructured":"Lombaert, H., et\u00a0al.: Diffeomorphic spectral matching of cortical surfaces. In: Information Processing in Medical Imaging: 23rd International Conference, IPMI 2013, Asilomar, CA, USA, June 28\u2013July 3, 2013. Proceedings 23. pp. 376\u2013389. Springer (2013)","DOI":"10.1007\/978-3-642-38868-2_32"},{"key":"25_CR28","doi-asserted-by":"crossref","unstructured":"Lyu, I., et\u00a0al.: Robust estimation of group-wise cortical correspondence with an application to macaque and human neuroimaging studies. Frontiers in neuroscience 9, \u00a0210 (2015)","DOI":"10.3389\/fnins.2015.00210"},{"key":"25_CR29","doi-asserted-by":"crossref","unstructured":"Margulies, D.S., et\u00a0al.: Situating the default-mode network along a principal gradient of macroscale cortical organization. Proceedings of the National Academy of Sciences 113(44), 12574\u201312579 (2016)","DOI":"10.1073\/pnas.1608282113"},{"key":"25_CR30","doi-asserted-by":"crossref","unstructured":"Plaze, M., et\u00a0al.: \u201cWhere do auditory hallucinations come from?\u201d-a brain morphometry study of schizophrenia patients with inner or outer space hallucinations. Schizophrenia Bulletin 37(1), 212\u2013221 (2011)","DOI":"10.1093\/schbul\/sbp081"},{"key":"25_CR31","doi-asserted-by":"crossref","unstructured":"Ren, J., et\u00a0al.: Sugar: Spherical ultrafast graph attention framework for cortical surface registration. Medical Image Analysis p. 103122 (2024)","DOI":"10.1016\/j.media.2024.103122"},{"key":"25_CR32","doi-asserted-by":"crossref","unstructured":"Robinson, E.C., et\u00a0al.: Multimodal surface matching with higher-order smoothness constraints. Neuroimage 167 (2018)","DOI":"10.1016\/j.neuroimage.2017.10.037"},{"key":"25_CR33","doi-asserted-by":"crossref","unstructured":"Robinson, E.C., et\u00a0al.: MSM: A new flexible framework for multimodal surface matching. Neuroimage 100, 414\u2013426 (2014)","DOI":"10.1016\/j.neuroimage.2014.05.069"},{"key":"25_CR34","doi-asserted-by":"crossref","unstructured":"Robinson, E.C., et\u00a0al.: Discrete optimisation for group-wise cortical surface atlasing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. pp.\u00a02\u20138 (2016)","DOI":"10.1109\/CVPRW.2016.62"},{"key":"25_CR35","doi-asserted-by":"crossref","unstructured":"Suliman, M.A., et\u00a0al.: A Deep-Discrete learning framework for spherical surface registration. In: Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2022. pp. 119\u2013129. Springer Nature Switzerland (2022)","DOI":"10.1007\/978-3-031-16446-0_12"},{"key":"25_CR36","unstructured":"Thual, A., et\u00a0al.: Aligning individual brains with fused unbalanced Gromov Wasserstein. Advances in Neural Information Processing Systems 35, 21792\u201321804 (2022)"},{"key":"25_CR37","doi-asserted-by":"crossref","unstructured":"Van Der\u00a0Meer, D., et\u00a0al.: The genetic architecture of human cortical folding. Science advances 7(51), eabj9446 (2021)","DOI":"10.1126\/sciadv.abj9446"},{"key":"25_CR38","doi-asserted-by":"crossref","unstructured":"Wang, Q.: Groupwise registration based on hierarchical image clustering and atlas synthesis. Human brain mapping 31(8), 1128\u20131140 (2010)","DOI":"10.1002\/hbm.20923"},{"key":"25_CR39","unstructured":"Williams, L.Z., et\u00a0al.: Structural and functional asymmetry of the neonatal cerebral cortex. Nature Human Behaviour pp. 1\u201314 (2023)"},{"key":"25_CR40","doi-asserted-by":"crossref","unstructured":"Wolz, R., et\u00a0al.: Leap: learning embeddings for atlas propagation. NeuroImage 49(2), 1316\u20131325 (2010)","DOI":"10.1016\/j.neuroimage.2009.09.069"},{"key":"25_CR41","doi-asserted-by":"crossref","unstructured":"Wright, R., et\u00a0al.: Construction of a fetal spatio-temporal cortical surface atlas from in utero MRI: Application of spectral surface matching. NeuroImage 120, 467\u2013480 (2015)","DOI":"10.1016\/j.neuroimage.2015.05.087"},{"key":"25_CR42","doi-asserted-by":"crossref","unstructured":"Wu, G., et\u00a0al.: SharpMean: groupwise registration guided by sharp mean image and tree-based registration. Neuroimage 56(4), 1968\u20131981 (Jun 2011)","DOI":"10.1016\/j.neuroimage.2011.03.050"},{"key":"25_CR43","doi-asserted-by":"crossref","unstructured":"Yeo, B.T.T., et\u00a0al.: Spherical demons: fast diffeomorphic landmark-free surface registration. IEEE Trans. Med. Imaging 29(3), 650\u2013668 (2010)","DOI":"10.1109\/TMI.2009.2030797"},{"key":"25_CR44","doi-asserted-by":"crossref","unstructured":"Ying, S., et\u00a0al.: Hierarchical unbiased graph shrinkage (HUGS): a novel groupwise registration for large data set. NeuroImage 84, 626\u2013638 (2014)","DOI":"10.1016\/j.neuroimage.2013.09.023"},{"key":"25_CR45","doi-asserted-by":"crossref","unstructured":"Zhao, F., et\u00a0al.: S3Reg: Superfast spherical surface registration based on deep learning. IEEE Trans. Med. Imaging 40(8), 1964\u20131976 (Aug 2021)","DOI":"10.1109\/TMI.2021.3069645"},{"key":"25_CR46","doi-asserted-by":"crossref","unstructured":"Zhao, F., et\u00a0al.: S3Reg: superfast spherical surface registration based on deep learning. IEEE transactions on medical imaging 40(8), 1964\u20131976 (2021)","DOI":"10.1109\/TMI.2021.3069645"}],"container-title":["Lecture Notes in Computer Science","Biomedical Image Registration"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73480-9_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,4]],"date-time":"2024-10-04T08:11:46Z","timestamp":1728029506000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73480-9_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031734793","9783031734809"],"references-count":46,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73480-9_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"5 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WBIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Biomedical Image Registration","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","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":"6 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wbir2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.wbir.info\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}