{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T10:07:14Z","timestamp":1750673234356,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031112027"},{"type":"electronic","value":"9783031112034"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-11203-4_4","type":"book-chapter","created":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T17:04:11Z","timestamp":1657299851000},"page":"29-34","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Towards a\u00a04D Spatio-Temporal Atlas of\u00a0the\u00a0Embryonic and\u00a0Fetal Brain Using a\u00a0Deep Learning Approach for\u00a0Groupwise Image Registration"],"prefix":"10.1007","author":[{"given":"Wietske A. P.","family":"Bastiaansen","sequence":"first","affiliation":[]},{"given":"Melek","family":"Rousian","sequence":"additional","affiliation":[]},{"given":"R\u00e9gine P. M.","family":"Steegers-Theunissen","sequence":"additional","affiliation":[]},{"given":"Wiro J.","family":"Niessen","sequence":"additional","affiliation":[]},{"given":"Anton H. J.","family":"Koning","sequence":"additional","affiliation":[]},{"given":"Stefan","family":"Klein","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,7,9]]},"reference":[{"key":"4_CR1","unstructured":"Balci, S.K., Golland, P., Shenton, M.E., Wells, W.M.: Free-form B-spline deformation model for groupwise registration. Med. Image Comput. Comput. Assist. Interv. 10, 23\u201330 (2007)"},{"key":"4_CR2","doi-asserted-by":"crossref","unstructured":"Bastiaansen, W.A., Rousian, M., Steegers-Theunissen, R.P., Niessen, W.J., Koning, A.H., Klein, S.: Multi-atlas segmentation and spatial alignment of the human embryo in first trimester 3D ultrasound. arXiv:2202.06599 (2022)","DOI":"10.59275\/j.melba.2022-cb15"},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Bhatia, K., Hajnal, J., Puri, B., Edwards, A., Rueckert, D.: Consistent groupwise non-rigid registration for atlas construction. In: 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro, vol. 1, pp. 908\u2013911 (2004)","DOI":"10.1109\/ISBI.2004.1398686"},{"key":"4_CR4","unstructured":"Dalca, A., Rakic, M., Guttag, J., Sabuncu, M.: Learning conditional deformable templates with convolutional networks. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"issue":"1","key":"4_CR5","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.media.2013.08.004","volume":"18","author":"E Dittrich","year":"2014","unstructured":"Dittrich, E., et al.: A spatio-temporal latent atlas for semi-supervised learning of fetal brain segmentations and morphological age estimation. Med. Image Anal. 18(1), 9\u201321 (2014)","journal-title":"Med. Image Anal."},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Gholipour, A.: A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth. Sci. Rep. 7(1), 1\u201313 (2017)","DOI":"10.1038\/s41598-017-00525-w"},{"issue":"2","key":"4_CR7","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1016\/j.neuroimage.2010.06.054","volume":"53","author":"PA Habas","year":"2010","unstructured":"Habas, P.A., et al.: A spatiotemporal atlas of MR intensity, tissue probability and shape of the fetal brain with application to segmentation. Neuroimage 53(2), 460\u2013470 (2010)","journal-title":"Neuroimage"},{"key":"4_CR8","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1016\/j.neuroimage.2018.08.030","volume":"185","author":"S Khan","year":"2019","unstructured":"Khan, S., et al.: Fetal brain growth portrayed by a spatiotemporal diffusion tensor MRI atlas computed from in utero images. Neuroimage 185, 593\u2013608 (2019)","journal-title":"Neuroimage"},{"issue":"5","key":"4_CR9","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1093\/humrep\/dew043","volume":"31","author":"I Koning","year":"2016","unstructured":"Koning, I., et al.: Growth trajectories of the human embryonic head and periconceptional maternal conditions. Hum. Reprod. 31(5), 968\u2013976 (2016)","journal-title":"Hum. Reprod."},{"issue":"6","key":"4_CR10","doi-asserted-by":"publisher","first-page":"1230","DOI":"10.1093\/humrep\/dex079","volume":"32","author":"I Koning","year":"2017","unstructured":"Koning, I., Dudink, J., Groenenberg, I., Willemsen, S., Reiss, I., Steegers-Theunissen, R.: Prenatal cerebellar growth trajectories and the impact of periconceptional maternal and fetal factors. Hum. Reprod. 32(6), 1230\u20131237 (2017)","journal-title":"Hum. Reprod."},{"issue":"4","key":"4_CR11","doi-asserted-by":"publisher","first-page":"2750","DOI":"10.1016\/j.neuroimage.2010.10.019","volume":"54","author":"M Kuklisova-Murgasova","year":"2011","unstructured":"Kuklisova-Murgasova, M., et al.: A dynamic 4D probabilistic atlas of the developing brain. Neuroimage 54(4), 2750\u20132763 (2011)","journal-title":"Neuroimage"},{"key":"4_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1007\/978-3-030-00807-9_8","volume-title":"Data Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis","author":"AIL Namburete","year":"2018","unstructured":"Namburete, A.I.L., van Kampen, R., Papageorghiou, A.T., Papie\u017c, B.W.: Multi-channel groupwise registration to construct an ultrasound-specific fetal brain atlas. In: Melbourne, A., et al. (eds.) PIPPI\/DATRA -2018. LNCS, vol. 11076, pp. 76\u201386. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00807-9_8"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Paladini, D., Malinger, G., Birnbaum, R., Monteagudo, A., Pilu, G., Salomon, L.: ISUOG practice guidelines (updated): sonographic examination of the fetal central nervous system. Part 1: performance of screening examination and indications for targeted neurosonography. Ultrasound Obstet. Gynecol. 56, 476\u2013484 (2020)","DOI":"10.1002\/uog.22145"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Rousian, M., et al.: Cohort profile update: the Rotterdam Periconceptional Cohort and embryonic and fetal measurements using 3D ultrasound and virtual reality techniques. Int. J. Epidemiol. 50, 1\u201314 (2021)","DOI":"10.1093\/ije\/dyab030"},{"issue":"1","key":"4_CR15","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1002\/uog.8831","volume":"37","author":"LJ Salomon","year":"2011","unstructured":"Salomon, L.J., et al.: Practice guidelines for performance of the routine mid-trimester fetal ultrasound scan. Ultrasound Obstet. Gynecol. 37(1), 116\u2013126 (2011)","journal-title":"Ultrasound Obstet. Gynecol."},{"issue":"3","key":"4_CR16","doi-asserted-by":"publisher","first-page":"2255","DOI":"10.1016\/j.neuroimage.2011.09.062","volume":"59","author":"A Serag","year":"2012","unstructured":"Serag, A., et al.: Construction of a consistent high-definition Spatio-temporal atlas of the developing brain using adaptive kernel regression. Neuroimage 59(3), 2255\u20132265 (2012)","journal-title":"Neuroimage"},{"key":"4_CR17","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1093\/ije\/dyv147","volume":"45","author":"R Steegers-Theunissen","year":"2016","unstructured":"Steegers-Theunissen, R., et al.: Cohort profile: the Rotterdam Periconceptional cohort (predict study). Int. J. Epidemiol. 45, 374\u2013381 (2016)","journal-title":"Int. J. Epidemiol."},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Uus, A., et al.: Multi-channel 4D parametrized atlas of macro-and microstructural neonatal brain development. Frontiers Neurosci., 721 (2021)","DOI":"10.1101\/2021.02.11.430835"},{"key":"4_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.118412","volume":"241","author":"J Wu","year":"2021","unstructured":"Wu, J., et al.: Age-specific structural fetal brain atlases construction and cortical development quantification for Chinese population. Neuroimage 241, 118412 (2021)","journal-title":"Neuroimage"}],"container-title":["Lecture Notes in Computer Science","Biomedical Image Registration"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-11203-4_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,28]],"date-time":"2024-09-28T20:37:16Z","timestamp":1727555836000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-11203-4_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031112027","9783031112034"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-11203-4_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"9 July 2022","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":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wbir2022","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"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Open Review","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"32","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":"11","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":"17","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":"34% - 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":"3-2","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)"}}]}}