Abstract
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 are performed manually and rely heavily on the operator’s skill. In this work, we propose an automated pipeline as an assistive system. By using a modified Faster R-CNN network, we trained a model 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.
C.K. Wong and M. Lin—These authors contributed equally to this work.
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Wong, C.K. et al. (2023). An Automatic Guidance and Quality Assessment System for Doppler Imaging of Umbilical Artery. In: Kainz, B., Noble, A., Schnabel, J., Khanal, B., Müller, J.P., Day, T. (eds) Simplifying Medical Ultrasound. ASMUS 2023. Lecture Notes in Computer Science, vol 14337. Springer, Cham. https://doi.org/10.1007/978-3-031-44521-7_2
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