{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T18:32:21Z","timestamp":1766428341517,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031171161"},{"type":"electronic","value":"9783031171178"}],"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\/978-3-031-17117-8_5","type":"book-chapter","created":{"date-parts":[[2022,9,21]],"date-time":"2022-09-21T23:35:39Z","timestamp":1663803339000},"page":"48-59","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Automated Segmentation of\u00a0Cervical Anatomy to\u00a0Interrogate Preterm Birth"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7196-5350","authenticated-orcid":false,"given":"Alicia B.","family":"Dagle","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0235-9247","authenticated-orcid":false,"given":"Yucheng","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9557-0660","authenticated-orcid":false,"given":"David","family":"Crosby","sequence":"additional","affiliation":[]},{"given":"Helen","family":"Feltovich","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4274-5786","authenticated-orcid":false,"given":"Michael","family":"House","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5236-9673","authenticated-orcid":false,"given":"Qi","family":"Yan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5989-0242","authenticated-orcid":false,"given":"Kristin M.","family":"Myers","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1839-6798","authenticated-orcid":false,"given":"Sachin","family":"Jambawalikar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,22]]},"reference":[{"key":"5_CR1","unstructured":"Cervical Length Education and Review Program. https:\/\/clear.perinatalquality.org"},{"key":"5_CR2","unstructured":"Labelbox: https:\/\/labelbox.com\/"},{"key":"5_CR3","unstructured":"MONAI - Home. https:\/\/monai.io\/"},{"key":"5_CR4","unstructured":"Preterm birth. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/preterm-birth"},{"issue":"9832","key":"5_CR5","doi-asserted-by":"publisher","first-page":"2162","DOI":"10.1016\/S0140-6736(12)60820-4","volume":"379","author":"H Blencowe","year":"2012","unstructured":"Blencowe, H., et al.: National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet 379(9832), 2162\u20132172 (2012). https:\/\/doi.org\/10.1016\/S0140-6736(12)60820-4","journal-title":"Lancet"},{"issue":"4","key":"5_CR6","doi-asserted-by":"publisher","first-page":"1566","DOI":"10.1542\/peds.2006-0860","volume":"118","author":"WM Callaghan","year":"2006","unstructured":"Callaghan, W.M., MacDorman, M.F., Rasmussen, S.A., Qin, C., Lackritz, E.M.: The contribution of preterm birth to infant mortality rates in the united states. Pediatrics 118(4), 1566\u20131573 (2006). https:\/\/doi.org\/10.1542\/peds.2006-0860","journal-title":"Pediatrics"},{"issue":"4","key":"5_CR7","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1080\/10255842.2015.1033163","volume":"19","author":"M Fernandez","year":"2016","unstructured":"Fernandez, M., et al.: Investigating the mechanical function of the cervix during pregnancy using finite element models derived from high-resolution 3D MRI. Comput. Methods Biomech. Biomed. Engin. 19(4), 404\u2013417 (2016). https:\/\/doi.org\/10.1080\/10255842.2015.1033163","journal-title":"Comput. Methods Biomech. Biomed. Engin."},{"key":"5_CR8","doi-asserted-by":"publisher","unstructured":"Hatamizadeh, A., et al.: UNETR: Transformers for 3D Medical Image Segmentation, October 2021. https:\/\/doi.org\/10.48550\/arXiv.2103.10504, arXiv:2103.10504 [cs, eess]","DOI":"10.48550\/arXiv.2103.10504"},{"key":"5_CR9","unstructured":"Institute of Medicine (US) Committee on Understanding Premature Birth and Assuring Healthy Outcomes: Preterm Birth: Causes, Consequences, and Prevention. The National Academies Collection: Reports funded by National Institutes of Health, National Academies Press (US), Washington (DC) (2007)"},{"key":"5_CR10","doi-asserted-by":"publisher","unstructured":"Kassabian, S., Fewer, S., Yamey, G., Brindis, C.D.: Building a global policy agenda to prioritize preterm birth: a qualitative analysis on factors shaping global health policymaking. Gates Open Res. 4, 65 (2020). https:\/\/doi.org\/10.12688\/gatesopenres.13098.1","DOI":"10.12688\/gatesopenres.13098.1"},{"key":"5_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1007\/978-3-030-12029-0_40","volume-title":"Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges","author":"E Kerfoot","year":"2019","unstructured":"Kerfoot, E., Clough, J., Oksuz, I., Lee, J., King, A.P., Schnabel, J.A.: Left-ventricle quantification using residual U-Net. In: Pop, M., et al. (eds.) STACOM 2018. LNCS, vol. 11395, pp. 371\u2013380. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-12029-0_40"},{"issue":"3","key":"5_CR12","doi-asserted-by":"publisher","first-page":"B2","DOI":"10.1016\/j.ajog.2016.04.027","volume":"215","author":"J McIntosh","year":"2016","unstructured":"McIntosh, J., Feltovich, H., Berghella, V., Manuck, T.: The role of routine cervical length screening in selected high- and low-risk women for preterm birth prevention. Am. J. Obstet. Gynecol. 215(3), B2\u2013B7 (2016). https:\/\/doi.org\/10.1016\/j.ajog.2016.04.027","journal-title":"Am. J. Obstet. Gynecol."},{"issue":"5","key":"5_CR13","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1053\/j.semperi.2009.06.007","volume":"33","author":"MT Mella","year":"2009","unstructured":"Mella, M.T., Berghella, V.: Prediction of preterm birth: cervical sonography. Semin. Perinatol. 33(5), 317\u2013324 (2009). https:\/\/doi.org\/10.1053\/j.semperi.2009.06.007","journal-title":"Semin. Perinatol."},{"issue":"9","key":"5_CR14","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1016\/j.jbiomech.2015.02.065","volume":"48","author":"KM Myers","year":"2015","unstructured":"Myers, K.M., et al.: The mechanical role of the cervix in pregnancy. J. Biomech. 48(9), 1511\u20131523 (2015). https:\/\/doi.org\/10.1016\/j.jbiomech.2015.02.065","journal-title":"J. Biomech."},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Myronenko, A.: 3D MRI brain tumor segmentation using autoencoder regularization. arXiv:1810.11654 [cs, q-bio], November 2018","DOI":"10.1007\/978-3-030-11726-9_28"},{"key":"5_CR16","unstructured":"Norwitz, E.: UpToDate. UpToDate, Waltham, MA (2015). http:\/\/www.uptodate.com\/contents\/prevention-of-spontaneous-preterm-birth, section: Prevention of spontaneous preterm birth"},{"key":"5_CR17","unstructured":"Oktay, O., et al.: Attention U-Net: Learning Where to Look for the Pancreas, May 2018. arXiv:1804.03999 [cs]"},{"key":"5_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"issue":"4","key":"5_CR19","doi-asserted-by":"publisher","first-page":"377.e1","DOI":"10.1016\/j.ajog.2008.10.038","volume":"200","author":"HN Simhan","year":"2009","unstructured":"Simhan, H.N., Krohn, M.A.: First-trimester cervical inflammatory milieu and subsequent early preterm birth. Am. J. Obstet. Gynecol. 200(4), 377.e1-377.e4 (2009). https:\/\/doi.org\/10.1016\/j.ajog.2008.10.038","journal-title":"Am. J. Obstet. Gynecol."},{"key":"5_CR20","doi-asserted-by":"publisher","unstructured":"Son, M., Miller, E.S.: Predicting preterm birth: cervical length and fetal fibronectin. Sem. Perinatol. 41(8), 445\u2013451 (2017). https:\/\/doi.org\/10.1053\/j.semperi.2017.08.002, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0146000517300903","DOI":"10.1053\/j.semperi.2017.08.002"},{"key":"5_CR21","doi-asserted-by":"publisher","unstructured":"Spong, C.Y.: Prediction and prevention of recurrent spontaneous preterm birth. Obstet. Gynecol. 110(2 Part 1), 405\u2013415 (2007). https:\/\/doi.org\/10.1097\/01.AOG.0000275287.08520.4a","DOI":"10.1097\/01.AOG.0000275287.08520.4a"},{"issue":"1","key":"5_CR22","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1080\/10867651.2004.10487596","volume":"9","author":"A Telea","year":"2004","unstructured":"Telea, A.: An image inpainting technique based on the fast marching method. J. Graph. Tools 9(1), 23\u201334 (2004). https:\/\/doi.org\/10.1080\/10867651.2004.10487596","journal-title":"J. Graph. Tools"},{"issue":"2","key":"5_CR23","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.siny.2015.12.009","volume":"21","author":"J Vink","year":"2016","unstructured":"Vink, J., Feltovich, H.: Cervical etiology of spontaneous preterm birth. Semin. Fetal Neonatal. Med. 21(2), 106\u2013112 (2016). https:\/\/doi.org\/10.1016\/j.siny.2015.12.009","journal-title":"Semin. Fetal Neonatal. Med."},{"issue":"5","key":"5_CR24","doi-asserted-by":"publisher","DOI":"10.1115\/1.4036259","volume":"139","author":"AR Westervelt","year":"2017","unstructured":"Westervelt, A.R., et al.: A parameterized ultrasound-based finite element analysis of the mechanical environment of pregnancy. J. Biomech. Eng. 139(5), 051004 (2017). https:\/\/doi.org\/10.1115\/1.4036259","journal-title":"J. Biomech. Eng."},{"key":"5_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1007\/978-3-030-60334-2_27","volume-title":"Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis","author":"T W\u0142odarczyk","year":"2020","unstructured":"W\u0142odarczyk, T., et al.: Spontaneous preterm birth prediction using convolutional neural networks. In: Hu, Y., et al. (eds.) ASMUS\/PIPPI -2020. LNCS, vol. 12437, pp. 274\u2013283. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-60334-2_27"},{"issue":"5","key":"5_CR26","doi-asserted-by":"publisher","first-page":"586","DOI":"10.3390\/electronics10050586","volume":"10","author":"T W\u0142odarczyk","year":"2021","unstructured":"W\u0142odarczyk, T., et al.: Machine learning methods for preterm birth prediction: a review. Electronics 10(5), 586 (2021). https:\/\/doi.org\/10.3390\/electronics10050586","journal-title":"Electronics"},{"key":"5_CR27","doi-asserted-by":"publisher","unstructured":"Yost, N.P.,et al.: For the national institute of child health and human development, MFMUN: second-trimester cervical sonography: features other than cervical length to predict spontaneous preterm birth. Obstet. Gynecol. 103(3), 457\u2013462 (2004). https:\/\/doi.org\/10.1097\/01.AOG.0000113618.24824.fb","DOI":"10.1097\/01.AOG.0000113618.24824.fb"}],"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\/978-3-031-17117-8_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T15:04:53Z","timestamp":1681225493000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-17117-8_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031171161","9783031171178"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-17117-8_5","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":"22 September 2022","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":"Singapore","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","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":"18 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pippi2022","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","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"12","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":"1","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":"83% - 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":"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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}