Examination of the umbilical artery with Doppler ultrasonography is performed to investigate blood supply to the fetus through the umbilical cord, which is vital for the monitoring of fetal health. Such examination involves several steps that must be performed correctly: identifying suitable sites on the umbilical artery for the measurement, acquiring the blood flow curve in the form of a Doppler spectrum, and ensuring compliance to a set of quality standards. These steps rely heavily on the operator's skill, and the shortage of experienced sonographers has thus created a demand for machine assistance. In this work, we propose an automatic system to fill the gap. By using a modified Faster R-CNN network, we obtain an algorithm that can suggest locations suitable for Doppler measurement. Meanwhile, we have also developed a method for assessment of the Doppler spectrum's quality. The proposed system is validated on 657 images from a national ultrasound screening database, with results demonstrating its potential as a guidance system.

翻译：脐动脉多普勒超声检查用于通过脐带评估胎儿血供情况，这对监测胎儿健康至关重要。此类检查需正确完成多个步骤：在脐动脉上识别合适的测量位置、获取多普勒频谱形式的血流曲线、确保符合一系列质量标准。这些步骤高度依赖于操作者的技能，而经验丰富的超声技师短缺催生了对辅助系统的需求。本研究提出一种自动化系统以填补这一空白。通过采用改进的Faster R-CNN网络，我们获得了能推荐适合多普勒测量位置的算法，同时开发了多普勒频谱质量评估方法。该系统基于全国超声筛查数据库中的657幅图像进行验证，结果表明其具备作为引导系统的潜力。