{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:14:49Z","timestamp":1777490089182,"version":"3.51.4"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T00:00:00Z","timestamp":1689552000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T00:00:00Z","timestamp":1689552000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772180"],"award-info":[{"award-number":["61772180"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006087","name":"National Center on Birth Defects and Developmental Disabilities","doi-asserted-by":"publisher","award":["2019SK1010"],"award-info":[{"award-number":["2019SK1010"]}],"id":[{"id":"10.13039\/100006087","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-15491-x","type":"journal-article","created":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T09:01:48Z","timestamp":1689584508000},"page":"15629-15648","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Attention mechanism optimized neural network for automatic measurement of fetal anterior-neck-lower-jaw angle in nuchal translucency tests"],"prefix":"10.1007","volume":"83","author":[{"given":"Yu-lin","family":"Peng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shi","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying-chun","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling-yu","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long-mei","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,17]]},"reference":[{"issue":"7","key":"15491_CR1","doi-asserted-by":"publisher","first-page":"2328","DOI":"10.4103\/jfmpc.jfmpc_440_19","volume":"8","author":"P Malik","year":"2019","unstructured":"Amisha, Malik P, Pathania M, Rathaur VK (2019) Overview of artificial intelligence in medicine. J Family Med Prim Care 8(7):2328\u20132331. https:\/\/doi.org\/10.4103\/jfmpc.jfmpc_440_19","journal-title":"J Family Med Prim Care"},{"key":"15491_CR2","unstructured":"B R (2015) Fundamentals of Biostatistics, 8th edn Cengage Learning"},{"issue":"5","key":"15491_CR3","doi-asserted-by":"publisher","first-page":"1073","DOI":"10.1158\/1078-0432.CCR-17-2236","volume":"24","author":"K Chang","year":"2018","unstructured":"Chang K, Bai HX, Zhou H, Su C, Bi WL, Agbodza E, Kavouridis VK, Senders JT, Boaro A, Beers A, Zhang B, Capellini A, Liao W, Shen Q, Li X, Xiao B, Cryan J, Ramkissoon S, Ramkissoon L, Ligon K, Wen PY, Bindra RS, Woo J, Arnaout O, Gerstner ER, Zhang PJ, Rosen BR, Yang L, Huang RY, Kalpathy-Cramer J (2018) Residual convolutional neural network for the determination of idh status in low- and high-grade gliomas from mr imaging. Clin Cancer Res 24(5):1073\u20131081. https:\/\/doi.org\/10.1158\/1078-0432.Ccr-17-2236","journal-title":"Clin Cancer Res"},{"issue":"7","key":"15491_CR4","doi-asserted-by":"publisher","first-page":"2113","DOI":"10.1148\/rg.2017170077","volume":"37","author":"G Chartrand","year":"2017","unstructured":"Chartrand G, Cheng PM, Vorontsov E, Drozdzal M, Turcotte S, Pal CJ, Kadoury S, Tang A (2017) Deep learning: A primer for radiologists. Radiographics 37(7):2113\u20132131. https:\/\/doi.org\/10.1148\/rg.2017170077","journal-title":"Radiographics"},{"issue":"2","key":"15491_CR5","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1148\/radiol.2018171820","volume":"288","author":"G Choy","year":"2018","unstructured":"Choy G, Khalilzadeh O, Michalski M, Do S, Samir AE, Pianykh OS, Geis JR, Pandharipande PV, Brink JA, Dreyer KJ (2018) Current applications and future impact of machine learning in radiology. Radiology 288(2):318\u2013328. https:\/\/doi.org\/10.1148\/radiol.2018171820","journal-title":"Radiology"},{"key":"15491_CR6","doi-asserted-by":"publisher","unstructured":"Dash JK, Mukhopadhyay S, Gupta RD, Khandelwal N (2021) Content-based image retrieval system for hrct lung images: assisting radiologists in self-learning and diagnosis of interstitial lung diseases. Multimedia Tools and Applications, pp 1\u201330. https:\/\/doi.org\/10.1007\/s11042-020-10173-4","DOI":"10.1007\/s11042-020-10173-4"},{"key":"15491_CR7","doi-asserted-by":"publisher","unstructured":"Deng L (2014) Deep Learning: Methods and Applications. https:\/\/doi.org\/10.1561\/9781601988157","DOI":"10.1561\/9781601988157"},{"issue":"1","key":"15491_CR8","doi-asserted-by":"publisher","first-page":"100379","DOI":"10.1016\/j.cosrev.2021.100379","volume":"40","author":"S Dong","year":"2021","unstructured":"Dong S, Wang P, Abbas K (2021) A survey on deep learning and its applications. Comput Sci Rev 40(1):100379. https:\/\/doi.org\/10.1016\/j.cosrev.2021.100379","journal-title":"Comput Sci Rev"},{"key":"15491_CR9","doi-asserted-by":"publisher","unstructured":"EK J (2018) Data-mining and analytics: rising concerns over privacy and people\u2019s security. https:\/\/doi.org\/10.33774\/apsa-2019-fwthd-v3","DOI":"10.33774\/apsa-2019-fwthd-v3"},{"key":"15491_CR10","doi-asserted-by":"publisher","unstructured":"Freeman WT, Pasztor EC (2000) Learning low-level vision. In: International conference on computer vision. https:\/\/doi.org\/10.1109\/ICCV.1999.790414","DOI":"10.1109\/ICCV.1999.790414"},{"key":"15491_CR11","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.metabol.2017.01.011","volume":"69s","author":"P Hamet","year":"2017","unstructured":"Hamet P, Tremblay J (2017) Artificial intelligence in medicine. Metabolism 69s:36\u201340. https:\/\/doi.org\/10.1016\/j.metabol.2017.01.011","journal-title":"Metabolism"},{"key":"15491_CR12","doi-asserted-by":"publisher","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on computer vision and pattern recognition, pp 7132\u20137141. https:\/\/doi.org\/10.1109\/TPAMI.2019.2913372","DOI":"10.1109\/TPAMI.2019.2913372"},{"key":"15491_CR13","unstructured":"Jaderberg M, Simonyan K, Zisserman A (2015) Spatial transformer networks. Advances in neural information processing systems, p 28"},{"key":"15491_CR14","doi-asserted-by":"publisher","first-page":"106198","DOI":"10.1016\/j.asoc.2020.106198","volume":"91","author":"D Jain","year":"2020","unstructured":"Jain D, Kumar A, Garg G (2020) Sarcasm detection in mash-up language using soft-attention based bi-directional lstm and feature-rich cnn. Appl Soft Comput 91:106198. https:\/\/doi.org\/10.1016\/j.asoc.2020.106198","journal-title":"Appl Soft Comput"},{"issue":"4","key":"15491_CR15","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1016\/j.gie.2020.06.040","volume":"92","author":"V Kaul","year":"2020","unstructured":"Kaul V, Enslin S, Gross SA (2020) History of artificial intelligence in medicine. Gastrointest Endosc 92(4):807\u2013812. https:\/\/doi.org\/10.1016\/j.gie.2020.06.040","journal-title":"Gastrointest Endosc"},{"issue":"4","key":"15491_CR16","doi-asserted-by":"publisher","first-page":"244","DOI":"10.1007\/s13224-012-0341-7","volume":"63","author":"S Kore","year":"2013","unstructured":"Kore S, Hegde A, Kanavia D, Supe P, Parikh M, Nandanwar YS (2013) Effects of period of gestation and position of fetal neck on nuchal translucency measurement. J Obstet Gynaecol India 63(4):244\u20138. https:\/\/doi.org\/10.1007\/s13224-012-0341-7","journal-title":"J Obstet Gynaecol India"},{"key":"15491_CR17","doi-asserted-by":"publisher","unstructured":"Lakshmi PS, Geetha M, Menon N, Krishnan V, Nedungadi P (2018). https:\/\/doi.org\/10.1109\/ICACCI.2018.8554914","DOI":"10.1109\/ICACCI.2018.8554914"},{"issue":"7553","key":"15491_CR18","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436\u201344. https:\/\/doi.org\/10.1038\/nature14539","journal-title":"Nature"},{"key":"15491_CR19","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","volume":"42","author":"G Litjens","year":"2017","unstructured":"Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, van der Laak J, van Ginneken B, S\u00e1nchez CI (2017) a survey on deep learning in medical image analysis. Med Image Anal 42:60\u201388. https:\/\/doi.org\/10.1016\/j.media.2017.07.005","journal-title":"Med Image Anal"},{"key":"15491_CR20","unstructured":"Lockwood CJ, Moore T, Copel J (2020) https:\/\/www.ntqr.org\/MyFTP\/Documents\/NTCriteria.pdf"},{"issue":"5 Pt 1","key":"15491_CR21","doi-asserted-by":"publisher","first-page":"1066","DOI":"10.1016\/j.obstetgynecol.2003.08.004","volume":"102","author":"FD Malone","year":"2003","unstructured":"Malone FD, D\u2019Alton ME (2003) First-trimester sonographic screening for down syndrome. Obstet Gynecol 102(5 Pt 1):1066\u201379. https:\/\/doi.org\/10.1016\/j.obstetgynecol.2003.08.004","journal-title":"Obstet Gynecol"},{"key":"15491_CR22","doi-asserted-by":"crossref","unstructured":"Maqueda AI, Loquercio A, Gallego G, Garcia N, Scaramuzza D (2018) Event-based vision meets deep learning on steering prediction for self-driving cars","DOI":"10.1109\/CVPR.2018.00568"},{"issue":"2","key":"15491_CR23","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1111\/jcpe.13406","volume":"48","author":"L Marini","year":"2021","unstructured":"Marini L, Tonetti MS, Nibali L, Rojas MA, Aimetti M, Cairo F, Cavalcanti R, Crea A, Ferrarotti F, Graziani F (2021) The staging and grading system in defining periodontitis cases: consistency and accuracy amongst periodontal experts, general dentists and undergraduate students. J Clin Periodontol 48(2):205\u2013215. https:\/\/doi.org\/10.1109\/CVPR.2018.00568","journal-title":"J Clin Periodontol"},{"key":"15491_CR24","unstructured":"Mnih V, Heess N, Graves A, Kavukcuoglu K (2014) Recurrent models of visual attention. Adv Neural Inf Process Syst, p 3"},{"issue":"sup1","key":"15491_CR25","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1080\/24699322.2016.1240317","volume":"21","author":"S Nie","year":"2016","unstructured":"Nie S, Yu J, Chen P, Wang Y, Zhang JQ (2016) A hessian plate filter and shape feature-based approach to automatically localizing the nt voi of 3d ultrasound data. Comput Assist Surg 21(sup1):83\u201391. https:\/\/doi.org\/10.1080\/24699322.2016.1240317","journal-title":"Comput Assist Surg"},{"issue":"1","key":"15491_CR26","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1016\/j.ultrasmedbio.2016.08.034","volume":"43","author":"S Nie","year":"2017","unstructured":"Nie S, Yu J, Chen P, Wang Y, Zhang JQ (2017) Automatic detection of standard sagittal plane in the first trimester of pregnancy using 3-d ultrasound data. Ultrasound Med Biol 43(1):286\u2013300. https:\/\/doi.org\/10.1016\/j.ultrasmedbio.2016.08.034","journal-title":"Ultrasound Med Biol"},{"key":"15491_CR27","doi-asserted-by":"publisher","unstructured":"Nie S, Yu J, Wang Y, Zhang J, Chen P (2014) Shape model and marginal space of 3d ultrasound volume data for automatically detecting a fetal head. In: 2014 International conference on audio, language and image processing, pp 681\u2013685. https:\/\/doi.org\/10.1109\/ICALIP.2014.7009881","DOI":"10.1109\/ICALIP.2014.7009881"},{"issue":"1","key":"15491_CR28","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1046\/j.1469-0705.1995.05010015.x","volume":"5","author":"PP Pandya","year":"1995","unstructured":"Pandya PP, Kondylios A, Hilbert L, Snijders RJ, Nicolaides KH (1995) Chromosomal defects and outcome in 1015 fetuses with increased nuchal translucency. Ultrasound Obstet Gynecol 5(1):15\u20139. https:\/\/doi.org\/10.1046\/j.1469-0705.1995.05010015.x","journal-title":"Ultrasound Obstet Gynecol"},{"key":"15491_CR29","unstructured":"Papadopoulos A, Korus P, Memon N (2021) Hard-attention for scalable image classification. Adv Neural Inf Process Syst, p 34"},{"issue":"1","key":"15491_CR30","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.artmed.2015.07.003","volume":"65","author":"N Peek","year":"2015","unstructured":"Peek N, Combi C, Marin R, Bellazzi R (2015) Thirty years of artificial intelligence in medicine (aime) conferences: a review of research themes. Artif Intell Med 65(1):61\u201373. https:\/\/doi.org\/10.1016\/j.artmed.2015.07.003","journal-title":"Artif Intell Med"},{"issue":"02","key":"15491_CR31","doi-asserted-by":"publisher","first-page":"141","DOI":"10.3760\/cma.j.cn113903-20200524-00487","volume":"24","author":"Y Peng","year":"2021","unstructured":"Peng Y, Zeng S, Luo Y (2021) Diagnosis and treatment for incarceration of retroverted uterus during pregnancy: a report of four cases. Chinese Journal of Perinatal Medicine 24 (02):141\u2013146. https:\/\/doi.org\/10.3760\/cma.j.cn113903-20200524-00487","journal-title":"Chinese Journal of Perinatal Medicine"},{"issue":"10","key":"15491_CR32","doi-asserted-by":"publisher","first-page":"3645","DOI":"10.1007\/s00431-022-04547-z","volume":"181","author":"Y Peng","year":"2022","unstructured":"Peng Y, Huang B, Luo Y, Huang X, Yao L, Zeng S (2022) Cross-sectional reference values of cerebral ventricle for Chinese neonates born at 25-41 weeks of gestation. Eur J Pediatr 181(10):3645\u20133654. https:\/\/doi.org\/10.1007\/s00431-022-04547-z","journal-title":"Eur J Pediatr"},{"issue":"5","key":"15491_CR33","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1308\/147870804290","volume":"86","author":"AN Ramesh","year":"2004","unstructured":"Ramesh AN, Kambhampati C, Monson JR, Drew PJ (2004) Artificial intelligence in medicine. Ann R Coll Surg Engl 86(5):334\u20138. https:\/\/doi.org\/10.1308\/147870804290","journal-title":"Ann R Coll Surg Engl"},{"key":"15491_CR34","unstructured":"Schlemper J, Oktay O, Chen L, Matthew J, Knight C, Kainz B, Glocker B, Rueckert D (2018) Attention-gated networks for improving ultrasound scan plane detection. arXiv:http:\/\/arxiv.org\/abs\/1804.05338"},{"key":"15491_CR35","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1016\/j.ins.2020.11.026","volume":"569","author":"J Shen","year":"2020","unstructured":"Shen J, Robertson N (2020) Bbas: Towards large scale effective ensemble adversarial attacks against deep neural network learning. Inf Sci 569:469\u2013478. https:\/\/doi.org\/10.1016\/j.ins.2020.11.026","journal-title":"Inf Sci"},{"key":"15491_CR36","doi-asserted-by":"publisher","first-page":"3417","DOI":"10.1109\/embc.2017.8037590","volume":"2017","author":"N Siqing","year":"2017","unstructured":"Siqing N, Jinhua Y, Ping C, Yuanyuan W, Yi G, Jian Qiu Z (2017) Automatic measurement of fetal nuchal translucency from three-dimensional ultrasound data. Annu Int Conf IEEE Eng Med Biol Soc 2017:3417\u20133420. https:\/\/doi.org\/10.1109\/embc.2017.8037590","journal-title":"Annu Int Conf IEEE Eng Med Biol Soc"},{"key":"15491_CR37","doi-asserted-by":"publisher","unstructured":"Szegedy C, Wei L, Jia Y, Sermanet P, Rabinovich A (2015) Going deeper with convolutions. IEEE Computer Society. https:\/\/doi.org\/10.1109\/CVPR.2015.7298594","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"15491_CR38","doi-asserted-by":"publisher","unstructured":"Thamizhvani TR, Ahmed K, Hemalatha RJ, Dhivya A, Chandrasekaran R (2021) Enhancement of mri images of hamstring avulsion injury using histogram based techniques. Multimedia Tools and Applications (3). https:\/\/doi.org\/10.1007\/s11042-020-10459-7","DOI":"10.1007\/s11042-020-10459-7"},{"key":"15491_CR39","doi-asserted-by":"crossref","unstructured":"Wang Q, Wu B, Zhu P, Li P, Hu Q (2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)) Eca-net: Efficient channel attention for deep convolutional neural networks","DOI":"10.1109\/CVPR42600.2020.01155"},{"issue":"7","key":"15491_CR40","doi-asserted-by":"publisher","first-page":"3330","DOI":"10.1109\/TCYB.2019.2894498","volume":"50","author":"L Wang","year":"2020","unstructured":"Wang L, Qian X, Zhang Y, Shen J, Cao X (2020) Enhancing sketch-based image retrieval by cnn semantic re-ranking. IEEE Trans Cybern 50 (7):3330\u20133342. https:\/\/doi.org\/10.1109\/TCYB.2019.2894498","journal-title":"IEEE Trans Cybern"},{"issue":"8","key":"15491_CR41","doi-asserted-by":"publisher","first-page":"872","DOI":"10.1111\/j.1471-0528.1998.tb10232.x","volume":"105","author":"BJ Whitlow","year":"1998","unstructured":"Whitlow BJ, Chatzipapas IK, Economides DL (1998) The effect of fetal neck position on nuchal translucency measurement. Br J Obstet Gynaecol 105 (8):872\u20136. https:\/\/doi.org\/10.1111\/j.1471-0528.1998.tb10232.x","journal-title":"Br J Obstet Gynaecol"},{"key":"15491_CR42","unstructured":"Xu K, Ba J, Kiros R, Cho K, Courville A, Salakhutdinov R, Zemel R, Bengio Y (2015) Show, attend and tell: Neural image caption generation with visual attention. Computer Science, pp 2048\u20132057"},{"key":"15491_CR43","doi-asserted-by":"publisher","unstructured":"Yang X (2020) An overview of the attention mechanisms in computer vision. In: Journal of physics: Conference series, vol 1693, p 012173. IOP Publishing. https:\/\/doi.org\/10.1088\/1742-6596\/1693\/1\/012173","DOI":"10.1088\/1742-6596\/1693\/1\/012173"},{"key":"15491_CR44","doi-asserted-by":"publisher","unstructured":"Zhang Y, Li K, Li K, Wang L, Zhong B, Fu Y (2018) Image super-resolution using very deep residual channel attention networks. https:\/\/doi.org\/10.1007\/978-3-030-01234-2_18","DOI":"10.1007\/978-3-030-01234-2_18"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15491-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-15491-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15491-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T08:45:36Z","timestamp":1706690736000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-15491-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,17]]},"references-count":44,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2024,2]]}},"alternative-id":["15491"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-15491-x","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,17]]},"assertion":[{"value":"16 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 April 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 April 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}