Automatic three-dimensional breast ultrasound (ABUS) is an innovative method for assisted screening of veins in the lower extremities. However, reviewing the thousands of images produced by ABUS is not only time consuming but also easy to miss the venous vessels area with weak feature. In order to analyze the application value of deep convolution level set in ABUS image analysis of varicose vein of lower extremity, an automatic detection algorithm based on the deep convolution level set method is proposed in this paper. First, the experimental data is obtained through ABUS imaging of venous blood vessels. Then, deep convolutional neural network and level set method are combined for automatically realize the position detection and contour segmentation of veins. Finally, the three-dimensional reconstruction of venous vessels is performed according to the ABUS imaging physical parameters. Experimental results are shown that the combination of deep convolution neural network and level set method can obtain a clear and complete three-dimensional venous vascular network of the lower extremities, which has important clinical significance to assist doctors in formulating personalized treatment plans.