Method for automatically tracking muscle feather angle by combining convolutional neural network and Kalman filtering

The invention discloses a method for automatically tracking a muscle feather angle by combining a convolutional neural network and Kalman filtering. The method specifically comprises the following steps: (1) preprocessing an ultrasonic image; (2) carrying out muscular membrane detection; (3) obtaining a muscle fiber direction observation value; (4) carrying out muscle fiber direction correction; and (5) calculating a feather angle. According to the method, the direction of the current muscle fiber is measured by using the deep convolutional neural network, and tracking of the feather angle isachieved by combining with the Kalman filter. According to the method, the robustness of a feather angle calculation algorithm is improved, the application field of an automatic feather angle labelingalgorithm is expanded, and an automatic feather angle tracking method is provided for an ultrasonic image sequence with poor quality. 本发明公开了一种采用卷积神经网络与卡尔曼滤波相结合自动追踪肌肉羽状角的方法，具体包括以下步骤：(1)超声图像预处理；(2)肌膜检测；(3)肌纤维方向观测值获取；(4)肌纤维方向校正；