Haonan Yang

The robotic breast ultrasound scanning (RBUS) system can help sonographer in the early screening of breast cancer. However, it still faces rigorous safety concerns, including non-smooth scanning paths and improper contact force regulation. In this letter, we propose a new path optimization method to improve the scanning smoothness, as well as, a dynamic contact regulation strategy considering both the breast deformation and ultrasound images. For the path planning, the anti-radial scanning approach is first adopted to generate some initial path points together with their normal vectors; then, a dual-objective optimization function is formulated, which considers both the acceleration continuity and deviation of the path, to filter out local path anomalies. For the force control, a contact force-strain regression model is first proposed and used to predict the desired force between the breast and probe at each path point. While within the adjacent path points, an updating algorithm is introduced to dynamically adjust the contact force in real-time by surveying the confidence of the ultrasound image. Our experimental results show that the proposed methods can make the scanning path smoother, and obtain intimate probe-tissue contact with less desired force.

Robotic ultrasound-guided system improves surgical flexibility and accuracy. Ultrasound (US) calibration is the key to obtain spatial relationship and localization of US images. However, existing calibration methods mainly rely on an external tracker, which leads to complicated workflow and prone to error accumulation. In this paper, we proposed a robot-assisted automatic US calibration method. This method can automatically complete the US calibration without any external tracker, thus improving the calibration accuracy and simplifying the workflow. In addition, we propose an automatic image segmentation method incorporating prior knowledge. It automatically segments the features of the calibration model in the US image during the US scanning process, and ensures the smooth execution of the automatic robot calibration process. Specifically, we transformed the calibration problem into a point-to-point registration problem and conducted experiments using three different registration algorithms. The results show that the calibration accuracy of our method is 0.65±0.20 mm. Our method significantly reduces calibration time compared to manual calibration. We also compare the proposed method with state-of-the-art methods, and the results demonstrated that the proposed method performs better.