Quality control of fetal ultrasound images: Detection of abdomen anatomical landmarks using AdaBoost

A fetal ultrasound (US) biometry plane can be identified from the presence and absence of landmarks in the image. We propose an automated method of detecting two important anatomical landmarks (stomach bubble and umbilical vein) from the fetal ultrasound abdomen scan for the purpose of scoring the image quality. The implementation is based on the AdaBoost learning algorithm with an execution time less than 6 seconds. Evaluation performed on 2384 images shows detection of the stomach is more accurate compared to the umbilical vein and the approach worth further investigation for quality assurance framework.