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J."},{"key":"ref21","article-title":"Ensemble transfer learning for fetal head analysis: From segmentation to gestational age and weight prediction","volume":"12","author":"Alzubaidi","year":"Sep. 15, 2022","journal-title":"Diagnostics"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1002\/uog.10082","article-title":"Intra-and interobserver variability in fetal ultrasound measurements","volume":"39","author":"Sarris","year":"2012","journal-title":"Ultrasound Obstetr. Gynecol"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1109\/JBHI.2017.2703890","article-title":"Automatic fetal head circumference measurement in ultrasound using random forest and fast ellipse fitting","volume":"22","author":"Wang","year":"2018","journal-title":"IEEE J. Biomed. 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