Confidence-driven control of an ultrasound probe

We present a control framework for optimizing image quality during robotic ultrasound acquisitions. The quality of the ultrasound signal across the field of view is represented by a confidence map that is computed online from the B-mode frames, following a model of sound propagation. Moments extracted from this confidence map are used to design a control law for optimizing imaging quality, based on the task function approach. The proposed confidence control is combined with force and position control to build two illustrative applications. First, we use force control and confidence control in order to maintain a correct pressure and a good orientation of the probe during teleoperation. Thus, control is shared between a human operator and the robot. Then, we add an automatic positioning task, so that the quality is optimized while maintaining a target in the image center. We show experimentally that confidence-driven control can effectively optimize the acoustic window in real time. In addition, we show that it can improve the tracking robustness, by preventing the target from being shadowed. Finally, we present the results of experiments performed on a human volunteer.