FCN-based approach for the automatic segmentation of bone surfaces in ultrasound images.

Purpose: A new algorithm, based on fully convolutional networks (FCN), is proposed for the automatic localization of the bone interface in ultrasound (US) images. The aim of this paper is to compare and validate this method with (1) a manual segmentation and (2) a state-of-the-art method called confidence in phase symmetry (CPS).

Methods: The dataset used for this study was composed of 1738 US images collected from three volunteers and manually delineated by three experts.