Mitral regurgitation flow is a critical diagnostic tool cardiological disease. We proposed a Convolutional Nerural Network approach to estimate regurgitation flow to replace manual force of calculation. The work involves denoising the doppler images, extracting speed info from labels, recognizing the aliasing region, and finally estimating the flow.