Clinical workflow of sonographers performing fetal anomaly ultrasound scans: deep-learning-based analysis.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology(2022)

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摘要
We present a novel evaluation of the anomaly scan acquisition process using a deep-learning-based analysis of ultrasound video. We note wide variation in the number and sequence of structures obtained during routine second-trimester anomaly scans. Overall, each anomaly scan was found to be unique in its scanning sequence, suggesting that sonographers take advantage of the fetal position and acquire the standard planes according to their visibility rather than following a strict acquisition order. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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关键词
anatomy,artificial intelligence,automation,big data,clinical workflow,computer vision,data science,deep learning,image analysis,machine learning,neural network,obstetrics,pregnancy,screening,sonography,ultrasound
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