Autonomous Ultrasound Scanning using Bayesian Optimization and Hybrid Force Control

Ultrasound scanning is an imaging technique that aids medical professionals in diagnostics and interventional procedures. However, a trained human-in-the-loop (HITL) with a radiologist is required to perform the scanning procedure. We seek to create a novel ultrasound system that can provide imaging in the absence of a trained radiologist, say for patients in the field who suffered injuries after a natural disaster. One challenge of automating ultrasound scanning involves finding the optimal area to scan and then performing the actual scan. This task requires simultaneously maintaining contact with the surface while moving along it to capture high quality images. In this work, we present an automated Robotic Ultrasound System (RUS) to tackle these challenges. Our approach introduces a Bayesian Optimization framework to guide the probe to multiple points on the unknown surface. Our proposed framework collects the ultrasound images as well as the pose information at every probed point to estimate regions with high vessel density (information map) and the surface contour. Based on the information map and the surface contour, an area of interest is selected for scanning. Furthermore, to scan the proposed region, a novel 6-axis hybrid force-position controller is presented to ensure acoustic coupling. Lastly, we provide experimental results on two different phantom models to corroborate our approach.

I. Introduction

Ultrasonography has become an important medical imaging modality especially for diagnostics and interventional procedures because of its real-time feedback, portability and radiation-free nature. Ultrasound imaging, thus, has significant advantages over other techniques like Computed Tomography (CT) or Magnetic Resonance Imaging (MRI). Although ultrasound imaging systems have great capabilities, there is a strong dependence on the trained professional's (sonographer) skill. The sonographer needs to find an appropriate area on the patient to scan, thus moving the ultrasound probe within the area of interest, making subtle corrections to the probes pose, and providing safe, significant and accurate forces through the probe to maintain diagnosticable image quality and prevent patient injury. Such skilled workers are not present everywhere. Therefore, to reduce the involve-ment of experts, the Robotic Ultrasound System (RUS) is introduced. RUS is the fusion of a robotic system and an ultrasound station with its scanning probe attached to the robot end-effector as shown in Fig. 1. Robotic ultrasound scanning also improves accuracy, stability, repeatability and maneuverability in terms of ultrasound image acquisition. In recent years, a lot of research has been put into improving the autonomy of the RUS [1]–[3], [4]–[6]. But most of these mentioned systems are tele-operated and assistive with a human still required to navigate the US probe to the region of interest. Fig. 1:

A robotic ultrasound system (RUS), which consists of a 6-DoF UR3e serial manipulator and an ultrasound probe mounted to the robot end-effector.