Scanning Path Planning of the Robot for Breast Ultrasound Examination Based on Binocular Vision and NURBS

Ultrasonic scanning is the most commonly used method for detecting breast cancer. Traditional breast ultrasound mainly relies on manual examination, which requires doctors with rich clinical experience. The scanning path planning of the robot for breast ultrasound examination based on binocular vision and non-uniform rational B-Splines (NURBS) is proposed in this paper to solve the limitations of traditional examination methods. First, breast images are acquired by the binocular camera. The depth information of the images is obtained through stereo matching, and the 3D point cloud reconstruction of the breast model is completed. Second, the spatial index algorithm based on the K-dimension tree (Kd-tree) and uniform sampling method are selected to denoise and down-sample the point cloud model to complete the preliminary optimization of the model. The point cloud information for the scanning path is extracted according to the method of point cloud extraction and the principle of normal vector calculation. Then, the interpolation optimization of the scanning path based on the NURBS curve is completed. The optimized scanning path is transformed into the robot motion path. Finally, the robot motion is simulated and analyzed, and the experimental results show that the rationality of robot operation and the smoothness of robot motion meet the requirements of path planning defined in this paper. The error analysis experiment shows that the path planned by this method can ensure the efficiency and accuracy of ultrasound examination.