Fetal biometry by an inexperienced operator using two- and three-dimensional ultrasound-Reference-Cited by-同舟云学术

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Fetal biometry by an inexperienced operator using two- and three-dimensional ultrasound

Published:2010-02-24 Issue:5 Volume:35 Page:566-571
ISSN:0960-7692
Container-title:Ultrasound in Obstetrics and Gynecology
language:en
Short-container-title:Ultrasound Obstet Gynecol

Author:

Yang F.,Leung K. Y.,Lee Y. P.,Chan H. Y.,Tang M. H. Y.

Publisher

Wiley

Subject

Obstetrics and Gynaecology,Radiology Nuclear Medicine and imaging,Reproductive Medicine,General Medicine,Radiological and Ultrasound Technology

Reference17 articles.

1. Tomographic sonography of the fetus: Is it accurate enough to be a frontline screen for fetal malformation?;Benacerraf;J Ultrasound Med,2006

2. How sonographic tomography will change the face of obstetric sonography: a pilot study;Benacerraf;J Ultrasound Med,2005

3. Evolution of fetal ultrasonography;Avni;Eur Radiol,2007

4. Three-dimensional ultrasound in the evaluation of fetal anomalies;Dyson;Ultrasound Obstet Gynecol,2000

5. Volumetric (3D) imaging reduces inter- and intraobserver variation of fetal biometry measurements;Chan;Ultrasound Obstet Gynecol,2009

Cited by 28 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A sonographic evaluation on agreement and time efficiency of fetal central nervous system biometry using semi-automated five-dimensional ultrasound versus standard two-dimensional ultrasound in a Philippine tertiary hospital;Philippine Journal of Obstetrics and Gynecology;2024-04

2. Deep learning to estimate gestational age from fly‐to cineloop videos: A novel approach to ultrasound quality control;International Journal of Gynecology & Obstetrics;2024-01-08

3. Fast fetal head compounding from multi-view 3D ultrasound;Medical Image Analysis;2023-10

4. A Clinical Approach to Semiautomated Three-Dimensional Fetal Brain Biometry—Comparing the Strengths and Weaknesses of Two Diagnostic Tools: 5DCNS+TM and SonoCNSTM;Journal of Clinical Medicine;2023-08-16

5. Development of a Machine Learning Model for Sonographic Assessment of Gestational Age;JAMA Network Open;2023-01-04

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