Automatic segmentation and object classification with neural network for an airborne ultrasound imaging system

An airborne ultrasound imaging system using 16 ultrasonic sensors surrounding a region of interest (ROI) was introduced in previous work. It allows reconstructing reflectivity images of multiple objects in 2D using a synthetic aperture focusing technique. The aim of this work is to automatically segment objects from these images to determine their positioning and allow classification.