An Autonomous Robotic System for Aorta Ultrasound Screening with Deep Learning Segmentation

Abdominal aortic aneurysm consists in the enlargement of the abdominal aorta involving a local diameter greater than 3 cm. Despite the fact that most aneurysms are asymptomatic, such a pathology becomes critical in case of complications as embolization, occlusion and rupture. The diagnosis is commonly achieved by means of an ultrasound examination carried out by expert sonographers. We designed a robotic system that can autonomously perform the ultrasound screening of the abdominal aorta, measuring its diameter and therefore providing the early diagnosis of the aneurysm. We use an impedance-controlled collaborative robot to move the ultrasound probe on the patient's abdomen while a deep learning neural network segments the aorta in the ultrasound image and estimates the diameter. Our motion planning algorithm makes use of an artificial potential field that guides the robot to move the probe toward the generation of a good aorta view. Finally, we conducted several experiments to validate the feasibility of the proposed approach.