{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T13:50:48Z","timestamp":1780062648153,"version":"3.54.0"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2020,6,26]],"date-time":"2020-06-26T00:00:00Z","timestamp":1593129600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,6,26]],"date-time":"2020-06-26T00:00:00Z","timestamp":1593129600000},"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":["Neural Comput & Applic"],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1007\/s00521-020-05127-8","type":"journal-article","created":{"date-parts":[[2020,6,26]],"date-time":"2020-06-26T22:10:31Z","timestamp":1593209431000},"page":"2217-2228","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Automated cell division classification in early mouse and human embryos using convolutional neural networks"],"prefix":"10.1007","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6740-6548","authenticated-orcid":false,"given":"Jonas","family":"Malmsten","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikica","family":"Zaninovic","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiansheng","family":"Zhan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zev","family":"Rosenwaks","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Shan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,6,26]]},"reference":[{"key":"5127_CR1","unstructured":"cdc.gov (2018) Center for disease control and prevention\u2014 ART success rates for 2015. http:\/\/www.cdc.gov\/art\/reports\/. Accessed 2018"},{"key":"5127_CR2","unstructured":"sartcorsonline.com (2019) SART National summary report. https:\/\/www.sartcorsonline.com\/rptCSR_PublicMultYear.aspx?ClinicPKID=0. Accessed: 2019. [cited 2019]"},{"issue":"2","key":"5127_CR3","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1093\/humrep\/deg081","volume":"18","author":"J Land","year":"2003","unstructured":"Land J, Evers J (2003) Risks and complications in assisted reproduction techniques: report of an ESHRE consensus meeting. Human Reprod 18(2):455\u2013457","journal-title":"Human Reprod"},{"issue":"6163","key":"5127_CR4","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1038\/332459a0","volume":"332","author":"P Braude","year":"1988","unstructured":"Braude P, Bolton V, Moore S (1988) Human gene expression first occurs between the four-and eight-cell stages of preimplantation development. Nature 332(6163):459\u2013461","journal-title":"Nature"},{"issue":"12","key":"5127_CR5","doi-asserted-by":"publisher","first-page":"2652","DOI":"10.1093\/humrep\/16.12.2652","volume":"16","author":"K Lundin","year":"2001","unstructured":"Lundin K, Bergh C, Hardarson T (2001) Early embryo cleavage is a strong indicator of embryo quality in human IVF. Hum Reprod 16(12):2652\u20132657","journal-title":"Hum Reprod"},{"key":"5127_CR6","unstructured":"Veeck, L.I. and N. Zaninovic, Atlas of Human Blastocysts. 2007: CRC Press"},{"issue":"10","key":"5127_CR7","doi-asserted-by":"publisher","first-page":"2658","DOI":"10.1093\/humrep\/der256","volume":"26","author":"M Meseguer","year":"2011","unstructured":"Meseguer M et al (2011) The use of morphokinetics as a predictor of embryo implantation. Hum Reprod 26(10):2658\u20132671","journal-title":"Hum Reprod"},{"issue":"10","key":"5127_CR8","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.1038\/nbt.1686","volume":"28","author":"CC Wong","year":"2010","unstructured":"Wong CC et al (2010) Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage. Nat Biotech 28(10):1115\u20131121","journal-title":"Nat Biotech"},{"issue":"9535","key":"5127_CR9","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1016\/S0140-6736(06)69204-0","volume":"368","author":"R Rai","year":"2006","unstructured":"Rai R, Regan L (2006) Recurrent miscarriage. The Lancet 368(9535):601\u2013611","journal-title":"The Lancet"},{"key":"5127_CR10","doi-asserted-by":"crossref","unstructured":"Khosravi P et al. (2018) Robust automated assessment of human blastocyst quality using deep learning. bioRxiv, 2018: p. 394882","DOI":"10.1101\/394882"},{"key":"5127_CR11","unstructured":"Giusti A et al. (2009) Segmentation of human zygotes in hoffman modulation contrast images. In: Proc. of MIUA"},{"key":"5127_CR12","doi-asserted-by":"crossref","unstructured":"Giusti A et al. (2010) Blastomere segmentation and 3d morphology measurements of early embryos from hoffman modulation contrast image stacks. In: Biomedical imaging: from nano to macro, 2010 IEEE International Symposium on. 2010. IEEE","DOI":"10.1109\/ISBI.2010.5490225"},{"issue":"7","key":"5127_CR13","doi-asserted-by":"publisher","first-page":"1551","DOI":"10.1109\/TMI.2014.2317836","volume":"33","author":"F Moussavi","year":"2014","unstructured":"Moussavi F et al (2014) A unified graphical models framework for automated mitosis detection in human embryos. IEEE Trans Med Imaging 33(7):1551\u20131562","journal-title":"IEEE Trans Med Imaging"},{"issue":"11","key":"5127_CR14","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun Y et al (1998) Gradient-based learning applied to document recognition. Proc IEEE 86(11):2278\u20132324","journal-title":"Proc IEEE"},{"key":"5127_CR15","doi-asserted-by":"crossref","unstructured":"Szegedy C et al. (2015) Going deeper with convolutions. In: Proceedings of the IEEE conference on computer vision and pattern recognition","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"5127_CR16","doi-asserted-by":"crossref","unstructured":"He K et al. (2016) Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition","DOI":"10.1109\/CVPR.2016.90"},{"key":"5127_CR17","doi-asserted-by":"crossref","unstructured":"Khan A, Gould S, Salzmann M (2016) Deep convolutional neural networks for human embryonic cell counting. In: European conference on computer vision. 2016. Springer","DOI":"10.1007\/978-3-319-46604-0_25"},{"issue":"4","key":"5127_CR18","doi-asserted-by":"publisher","first-page":"e220","DOI":"10.1016\/j.fertnstert.2018.07.634","volume":"110","author":"J Gingold","year":"2018","unstructured":"Gingold J et al (2018) Predicting embryo morphokinetic annotations from time-lapse videos using convolutional neural networks. Fertil Steril 110(4):e220","journal-title":"Fertil Steril"},{"issue":"4","key":"5127_CR19","doi-asserted-by":"publisher","first-page":"e360","DOI":"10.1016\/j.fertnstert.2018.07.1005","volume":"110","author":"J Malmsten","year":"2018","unstructured":"Malmsten J et al (2018) Automatic prediction of embryo cell stages using artificial intelligence convolutional neural network. Fertil Steril 110(4):e360","journal-title":"Fertil Steril"},{"key":"5127_CR20","unstructured":"Lau T et al. (2019) Embryo staging with weakly-supervised region selection and dynamically-decoded predictions. arXiv preprint arXiv:1904.04419"},{"issue":"4","key":"5127_CR21","doi-asserted-by":"publisher","first-page":"e430","DOI":"10.1016\/j.fertnstert.2018.08.034","volume":"110","author":"A Tran","year":"2018","unstructured":"Tran A et al (2018) Artificial intelligence as a novel approach for embryo selection. Fertil Steril 110(4):e430","journal-title":"Fertil Steril"},{"key":"5127_CR22","doi-asserted-by":"crossref","unstructured":"Malmsten J et al. (2019) Automated cell stage predictions in early mouse and human embryos using convolutional neural networks. In: 2019 IEEE EMBS international conference on biomedical & health informatics (BHI). 2019. IEEE","DOI":"10.1109\/BHI.2019.8834541"},{"key":"5127_CR23","doi-asserted-by":"crossref","unstructured":"Szegedy C et al. (2016) Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE conference on computer vision and pattern recognition","DOI":"10.1109\/CVPR.2016.308"},{"key":"5127_CR24","unstructured":"Kingma D, Ba J (2014) Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"5127_CR25","unstructured":"Chollet F et al (2015) Keras.\u00a0https:\/\/keras.io"},{"key":"5127_CR26","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.compbiomed.2014.04.011","volume":"51","author":"M Cicconet","year":"2014","unstructured":"Cicconet M et al (2014) Label free cell-tracking and division detection based on 2d time-lapse images for lineage analysis of early embryo development. Comput Biol Med 51:24\u201334","journal-title":"Comput Biol Med"},{"key":"5127_CR27","doi-asserted-by":"crossref","unstructured":"Khan AS, Gould, Salzmann M (2015) Automated monitoring of human embryonic cells up to the 5-cell stage in time-lapse microscopy images. In: Biomedical imaging (ISBI), 2015 IEEE 12th international symposium on. 2015. IEEE","DOI":"10.1109\/ISBI.2015.7163894"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05127-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-020-05127-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-05127-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T23:41:36Z","timestamp":1624664496000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-020-05127-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,26]]},"references-count":27,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2021,4]]}},"alternative-id":["5127"],"URL":"https:\/\/doi.org\/10.1007\/s00521-020-05127-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,26]]},"assertion":[{"value":"7 February 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 June 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"Authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"IRB 19-04,020,098","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}