Image Analysis Using Machine Learning: Anatomical Landmarks Detection in Fetal Ultrasound Images

Abstract

Accurate and robust image analysis software is crucial for assessing the quality of ultrasound images of fetal biometry. In this work, we present the result of our automated image analysis method based on a machine learning algorithm in detecting important anatomical landmarks employed in manual scoring of ultrasound images of the fetal abdomen. Experimental results on 2384 images are promising and the clinical validation using 300 images demonstrates a high level agreement between the automated method and experts.