{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T18:49:34Z","timestamp":1774896574591,"version":"3.50.1"},"reference-count":20,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T00:00:00Z","timestamp":1628812800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Scientific Programming"],"published-print":{"date-parts":[[2021,8,13]]},"abstract":"In order to realize the automatic recognition and diagnosis in ultrasound images of fetal spina bifida, the U-Net algorithm was improved in this study to obtain a new convolutional neural network algorithm\u2014Oct-U-Net. 3,300 pregnant women were selected as the research objects, who underwent three-dimensional (3D) ultrasound examinations. Then, Oct-U-Net was applied to evaluate the diagnostic effect of fetal spina bifida by recall rate, precise rate, mean standard error, pixel accuracy (PA), mean intersection over union (MIoU), and running time. Besides, the fully convolutional network (FCN) algorithm and the U-Net algorithm were introduced for comparison. Results showed that recall rate, precise rate, PA, and MioU of Oct-U-Net were 0.93, 0.96, 0.949, and 0.917, respectively, which were markedly higher than those of FCN and U-Net \n \n \n \n P<\/a:mi>\n <<\/a:mo>\n 0.05<\/a:mn>\n <\/a:mrow>\n <\/a:mfenced>\n <\/a:math>\n <\/jats:inline-formula>. The mean standard error of Oct-U-Net was 4.1243, and its average running time was 12.15 seconds. The values of the above two indicators were sharply lower than those of FCN and U-Net \n \n \n \n P<\/f:mi>\n <<\/f:mo>\n 0.05<\/f:mn>\n <\/f:mrow>\n <\/f:mfenced>\n <\/f:math>\n <\/jats:inline-formula>. In conclusion, Oct-U-Net had a better diagnostic effect on 3D ultrasound images of fetal spina bifida, with higher segmentation accuracy and shorter running time, so it was worthy of clinical application.<\/jats:p>","DOI":"10.1155\/2021\/3605739","type":"journal-article","created":{"date-parts":[[2021,8,16]],"date-time":"2021-08-16T05:28:11Z","timestamp":1629091691000},"page":"1-9","source":"Crossref","is-referenced-by-count":4,"title":["Neural Network Algorithm-Based Three-Dimensional Ultrasound Evaluation in the Diagnosis of Fetal Spina Bifida"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7972-6127","authenticated-orcid":true,"given":"Lei","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Ultrasound, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou 215008, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0966-7832","authenticated-orcid":true,"given":"Yingying","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou 215000, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3609-4494","authenticated-orcid":true,"given":"Yujie","family":"Deng","sequence":"additional","affiliation":[{"name":"Department of Ultrasound, The Affiliated Suzhou Science & Technology Town Hospital of Nanjing Medical University, Suzhou 215000, Jiangsu, China"}]}],"member":"311","reference":[{"issue":"4","key":"1","first-page":"62","article-title":"Three dimensional ultrasound imaging technology in the diagnosis of fetal spina bifida","volume":"20","author":"Y. X. Sun","year":"2015","journal-title":"China Health Standard Management"},{"issue":"28","key":"2","first-page":"264","article-title":"The application of conventional ultrasonography combined with three-dimensional ultrasound in diagnosis of fetal spina bifida during early pregnancy","volume":"5","author":"F. L. Ma","year":"2018","journal-title":"Diet Health"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1007\/s10730-017-9327-2"},{"issue":"2","key":"4","first-page":"195","article-title":"The value of prenatal ultrasonic diagnosis of fetal open and closed spina bifida","volume":"43","author":"C. Zhu","year":"2016","journal-title":"Fudan University Journal of Medical Sciences"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1159\/000491751"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1007\/s00404-020-05503-8"},{"issue":"6","key":"7","first-page":"41","article-title":"Ultrasound diagnosis value of open cleft spine and closed spina bifida","volume":"3","author":"X. T. 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Sha","year":"2017","journal-title":"Chinese Journal of Preventive Medicine"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.11896\/j.issn.1002-137X.2017.6A.055"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-66468-x"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.11772\/j.issn.1001-9081.2018112321"},{"issue":"8","key":"16","first-page":"36","article-title":"Ultrasound image segmentation for median nerves based on improved U-Net deep network","volume":"41","author":"B. Y. Tian","year":"2020","journal-title":"Process Automation Instrumentation"},{"issue":"9","key":"17","first-page":"2508","article-title":"Survey of convolutional neural network","volume":"36","author":"Y. D. Li","year":"2016","journal-title":"Journal of Computer Applications"},{"issue":"9","key":"18","first-page":"1178","article-title":"Learning performance of convolutional neural networks with different pooling models","volume":"21","author":"W. J. 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