{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T21:12:27Z","timestamp":1776201147482,"version":"3.50.1"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031455438","type":"print"},{"value":"9783031455445","type":"electronic"}],"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\/978-3-031-45544-5_2","type":"book-chapter","created":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T07:07:47Z","timestamp":1697008067000},"page":"17-27","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Deep Learning Approach for\u00a0Segmenting the\u00a0Subplate and\u00a0Proliferative Zones in\u00a0Fetal Brain MRI"],"prefix":"10.1007","author":[{"given":"Helena S.","family":"Sousa","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abi","family":"Fukami-Gartner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alena U.","family":"Uus","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vanessa","family":"Kyriakopoulou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brigita","family":"Ziukaite","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isa","family":"Anzak","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"O\u2019Muircheartaigh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph V.","family":"Hajnal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J-Donald","family":"Tournier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Hammers","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mary A.","family":"Rutherford","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria","family":"Deprez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,12]]},"reference":[{"key":"2_CR1","unstructured":"Developing human connectome project. http:\/\/www.developingconnectome.org"},{"key":"2_CR2","unstructured":"Mirtk software package. https:\/\/github.com\/BioMedIA\/MIRTK"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Bayer, S.A., Altman, J.: The Human Brain During the Third Trimester. CRC Press (2003)","DOI":"10.1201\/9780203494943"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Bayer, S.A., Altman, J.: The human brain during the second trimester (2005)","DOI":"10.1201\/9780203507483"},{"key":"2_CR5","unstructured":"Cardoso, M.J., et al.: Monai: An open-source framework for deep learning in healthcare. arXiv preprint arXiv:2211.02701 (2022)"},{"key":"2_CR6","unstructured":"Cordero-Grande, L., et al.: Automating motion compensation in 3T fetal brain imaging: localize, align and reconstruct. In: ISMRM 2019, p. 1000 (2019)"},{"key":"2_CR7","doi-asserted-by":"crossref","unstructured":"Gholipour, A., et al.: A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth. Sci. Rep. 7 (2017)","DOI":"10.1038\/s41598-017-00525-w"},{"key":"2_CR8","doi-asserted-by":"crossref","unstructured":"Griffiths, P.D., et al.: Sectional anatomy of the fetal brain (2010)","DOI":"10.1016\/B978-0-323-05296-2.50005-9"},{"issue":"2","key":"2_CR9","first-page":"782","volume":"62","author":"M Jenkinson","year":"2012","unstructured":"Jenkinson, M., et al.: FSl. Neuro Image 62(2), 782\u2013790 (2012)","journal-title":"Neuro Image"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Kostovi\u0107, I., et al.: Neural histology and neurogenesis of the human fetal and infant brain. Neuro Image 188, 743\u2013773 (2019)","DOI":"10.1016\/j.neuroimage.2018.12.043"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Machado-Rivas, F., et al.: Normal growth, sexual dimorphism, and lateral asymmetries at fetal brain MRI. Radiology 303, 162\u2013170 (2022)","DOI":"10.1148\/radiol.211222"},{"key":"2_CR12","unstructured":"Oktay, O., et al.: Attention U-Net: learning where to look for the pancreas. In: MIDDL 2016 (2018)"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Payette, K., et al.: An automatic multi-tissue human fetal brain segmentation benchmark using the fetal tissue annotation dataset. Sci. Data 8 (2021)","DOI":"10.1038\/s41597-021-00946-3"},{"key":"2_CR14","unstructured":"Price, A.N., et al.: The developing human connectome project (DHCP): fetal acquisition protocol. In: ISMRM 2019 (2019)"},{"key":"2_CR15","doi-asserted-by":"crossref","unstructured":"Rutherford, M., et al.: MR imaging methods for assessing fetal brain development (2008)","DOI":"10.1002\/dneu.20614"},{"key":"2_CR16","doi-asserted-by":"crossref","unstructured":"Stuempflen, M., et al.: The ganglionic eminence: volumetric assessment of transient brain structure utilizing fetal magnetic resonance imaging. Ultrasound in Obstet. & Gynecol. (2023)","DOI":"10.1002\/uog.26232"},{"key":"2_CR17","unstructured":"Uus, A., et al.: Multi-channel spatio-temporal MRI atlas of the normal fetal brain development from the developing human connectome project. G-Node (2023)"},{"key":"2_CR18","doi-asserted-by":"crossref","unstructured":"Uus, A.U., et al.: Bounti: brain volumetry and automated parcellation for 3D fetal MRI. biorxiv (2023)","DOI":"10.1101\/2023.04.18.537347"},{"key":"2_CR19","doi-asserted-by":"crossref","unstructured":"Vasung, L., et al.: Abnormal development of transient fetal zones in mild isolated fetal ventriculomegaly. Cereb. Cortex (2022)","DOI":"10.1093\/cercor\/bhac125"},{"key":"2_CR20","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.453","volume":"2","author":"S Van der Walt","year":"2014","unstructured":"Van der Walt, S., et al.: scikit-image: image processing in Python. PeerJ 2, e453 (2014)","journal-title":"PeerJ"},{"key":"2_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/978-3-030-00807-9_15","volume-title":"Data Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis","author":"R Wright","year":"2018","unstructured":"Wright, R., et al.: LSTM spatial co-transformer networks for registration of 3D Fetal US and MR brain images. In: PIPPI\/DATRA -2018. LNCS, vol. 11076, pp. 149\u2013159. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-00807-9_15"},{"key":"2_CR22","doi-asserted-by":"crossref","unstructured":"Yushkevich, P.A., et al.: User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuro Image 31, 1116\u20131128 (2006)","DOI":"10.1016\/j.neuroimage.2006.01.015"}],"container-title":["Lecture Notes in Computer Science","Perinatal, Preterm and Paediatric Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-45544-5_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T07:09:11Z","timestamp":1697008151000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-45544-5_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031455438","9783031455445"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-45544-5_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"12 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PIPPI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Preterm, Perinatal and Paediatric Image Analysis","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":"12 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":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pippi2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pippiworkshop.github.io\/","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 Microsoft","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"14","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":"10","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":"71% - 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":"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":"2","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}