Detection Method of Three-Dimensional Echocardiography Based on Deep Learning

الملخص EN

In order to improve the detection and recognition ability of 3D echocardiography, a method of 3D echocardiography detection based on depth learning is proposed.

The information conduction model of three-dimensional echocardiography is constructed.

The edge pixel feature matching method is used to extract the key information of echocardiography, and the information compensation method is used to repair the missing area of three-dimensional echocardiography information.

The feature decomposition and information fusion of 3D ultrasonic imaging are carried out by using five stage wavelet decomposition method, and the feature reconstruction and adaptive template matching of 3D echocardiography are processed by depth learning algorithm, modeling and detecting the rationality of three-dimensional echocardiography.

The simulation results show that this method has better detection performance; the accuracy of detection and recognition is high, which is more reasonable in the application of 3D echocardiography repair and detection recognition.