{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T15:20:38Z","timestamp":1779895238488,"version":"3.53.1"},"reference-count":14,"publisher":"Springer Science and Business Media LLC","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,17]]},"DOI":"10.7759\/cureus.45429","type":"journal-article","created":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T03:43:07Z","timestamp":1695008587000},"source":"Crossref","is-referenced-by-count":3,"title":["Microscopic Video-Based Grouped Embryo Segmentation: A Deep Learning Approach"],"prefix":"10.7759","author":[{"given":"Huy Phuong","family":"Tran","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hoang Thi","family":"Diem Tuyet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Truong Quang","family":"Dang Khoa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Le Nhi","family":"Lam Thuy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pham The","family":"Bao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vu Ngoc","family":"Thanh Sang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rbmo.2010.06.038","article-title":"Group culture of human zygotes is superior to individual culture in terms of blastulation, implantation and life birth","volume":"21","author":"Ebner T","year":"2010","unstructured":"Ebner T, Shebl O, Moser M, Mayer RB, Arzt W, Tews G. Group culture of human zygotes is superior to individual culture in terms of blastulation, implantation and life birth. Reprod Biomed Online. 2010, 21:762-8. 10.1016\/j.rbmo.2010.06.038","journal-title":"Reprod Biomed Online"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.102551","article-title":"Automated and precise recognition of human zygote cytoplasm: a robust image-segmentation system based on a convolutional neural network","volume":"67","author":"Zhao M.","year":"2021","unstructured":"Zhao M., Li H, Li R, et al.. Automated and precise recognition of human zygote cytoplasm: a robust image-segmentation system based on a convolutional neural network. Biomed Signal Process Control. 2021, 67:102551. 10.1016\/j.bspc.2021.102551","journal-title":"Biomed Signal Process Control"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.17671\/gazibtd.949430","article-title":"Comparison of u-net based models for human embryo segmentation","volume":"15","author":"Uysal N","year":"2022","unstructured":"Uysal N, Yozgatli TK, Yildizcan EN, Gezer M,  Ba\u015ftu E. Comparison of u-net based models for human embryo segmentation. Bili\u015fim Teknolojileri Dergisi. 2022, 15:35-44. 10.17671\/gazibtd.949430","journal-title":"Bili\u015fim Teknolojileri Dergisi"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10. 3390\/bdcc7020091","article-title":"Predicting cell cleavage timings from time-lapse videos of human embryos","volume":"7","author":"Sharma A","year":"2023","unstructured":"Sharma A, Ansari AZ, Kakulavarapu R, Stensen MH, Riegler MA, Hammer HL. Predicting cell cleavage timings from time-lapse videos of human embryos. Big Data Cogn Comput. 2023, 7:91. 10. 3390\/bdcc7020091","journal-title":"Big Data Cogn Comput"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3391743","article-title":"Video object segmentation and tracking: a survey","volume":"11","author":"Yao R","year":"2020","unstructured":"Yao R, Lin G, Xia S, Zhao J, Zhou Y. Video object segmentation and tracking: a survey. ACM Trans Intell Syst Technol. 2020, 11:1-47. 10.1145\/3391743","journal-title":"ACM Trans Intell Syst Technol"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10176-7","article-title":"Deep learning for video object segmentation: a review","volume":"56","author":"Gao M","year":"2023","unstructured":"Gao M, Zheng F, Yu JJ, Shan C, Ding G, Han J. Deep learning for video object segmentation: a review. Artif Intell Rev. 2023, 56:457-531. 10.1007\/s10462-022-10176-7","journal-title":"Artif Intell Rev"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1111\/jcmm.16288","article-title":"Application of convolutional neural network on early human embryo segmentation during in vitro fertilization","volume":"25","author":"Zhao M","year":"2021","unstructured":"Zhao M, Xu M, Li H, et al.. Application of convolutional neural network on early human embryo segmentation during in vitro fertilization. J Cell Mol Med. 2021, 25:2633-44. 10.1111\/jcmm.16288","journal-title":"J Cell Mol Med"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1017\/S0967199422000326","article-title":"Morphometric evaluation of two-pronucleus zygote images using image-processing techniques","volume":"30","author":"Sayadi N","year":"2022","unstructured":"Sayadi N, Monji-Azad S, Mirroshandel SA, Ghasemian F. Morphometric evaluation of two-pronucleus zygote images using image-processing techniques. Zygote. 2022, 30:819-29. 10.1017\/S0967199422000326","journal-title":"Zygote"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.105946","article-title":"A robust deep learning-based multiclass segmentation method for analyzing human metaphase II oocyte images","volume":"201","author":"Firuzinia S","year":"2021","unstructured":"Firuzinia S, Afzali SM, Ghasemian F, Mirroshandel SA. A robust deep learning-based multiclass segmentation method for analyzing human metaphase II oocyte images. Comput Methods Programs Biomed. 2021, 201:105946. 10.1016\/j.cmpb.2021.105946","journal-title":"Comput Methods Programs Biomed"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2018.8451750","article-title":"Multi-resolutional ensemble of stacked dilated u-net for inner cell mass segmentation in human embryonic images","author":"Rad RM","year":"2018","unstructured":"Rad RM, Saeedi P, Au J, Havelock J. Multi-resolutional ensemble of stacked dilated u-net for inner cell mass segmentation in human embryonic images. 25th IEEE International Conference on Image Processing. 2018, 3518-22. 10.1109\/ICIP.2018.8451750","journal-title":"25th IEEE International Conference on Image Processing"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/biomedicines10071717","article-title":"Human blastocyst components detection using multiscale aggregation semantic segmentation network for embryonic analysis","volume":"10","author":"Arsalan M","year":"2022","unstructured":"Arsalan M, Haider A, Cho SW, Kim YH, Park KR. Human blastocyst components detection using multiscale aggregation semantic segmentation network for embryonic analysis. Biomedicines. 2022, 10:1717. 10.3390\/biomedicines10071717","journal-title":"Biomedicines"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101612","article-title":"Trophectoderm segmentation in human embryo images via inceptioned U-Net","volume":"62","author":"Rad RM","year":"2020","unstructured":"Rad RM, Saeedi P, Au J, Havelock J. Trophectoderm segmentation in human embryo images via inceptioned U-Net. Med Image Anal. 2020, 62:101612. 10.1016\/j.media.2019.101612","journal-title":"Med Image Anal"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2207.02696","article-title":"YOLOv7: trainable bag-of- freebies sets new state-of-the-art for real-time object detectors [PREPRINT]","author":"Wang CY","year":"2022","unstructured":"Wang CY, Bochkovskiy A, Hong-Yuan ML. YOLOv7: trainable bag-of- freebies sets new state-of-the-art for real-time object detectors [PREPRINT]. arXiv preprint. 2022, 10.48550\/arXiv.2207.02696","journal-title":"arXiv preprint"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/SYSMART.2016.7894491","article-title":"Blur image detection using laplacian operator and open-CV","author":"Bansal R","year":"2016","unstructured":"Bansal R, Raj G, Choudhury T. Blur image detection using laplacian operator and open-CV. 2016 International Conference System Modeling &amp; Advancement in Research Trends (SMART). 2016, 63-7. 10.1109\/SYSMART.2016.7894491","journal-title":"2016 International Conference System Modeling & Advancement in Research Trends (SMART)"}],"container-title":["Cureus"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cureus.com\/articles\/188344-microscopic-video-based-grouped-embryo-segmentation-a-deep-learning-approach","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,9]],"date-time":"2024-02-09T20:05:08Z","timestamp":1707509108000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cureus.com\/articles\/188344-microscopic-video-based-grouped-embryo-segmentation-a-deep-learning-approach"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,17]]},"references-count":14,"URL":"https:\/\/doi.org\/10.7759\/cureus.45429","relation":{},"ISSN":["2168-8184"],"issn-type":[{"value":"2168-8184","type":"print"}],"subject":[],"published":{"date-parts":[[2023,9,17]]}}}