Breast ultrasound image tumor segmentation method based on cGAN

The invention discloses a breast ultrasound image tumor segmentation method based on cGAN. The method comprises the steps of breast ultrasound image data preprocessing, ultrasound image generation, deep neural network model construction, loss function definition, model training and result generation. In data preprocessing, a mode of firstly filling a mirror image and then cutting is used, so that the form of a breast tumor is not changed, and a breast ultrasonic image meeting the size requirement can be obtained. And on this basis, the ultrasonic image is continuously generated through the cGAN network. In the step of constructing the deep neural network model, the design mode of the GAN network is followed on the whole. The whole GANs framework can be regarded as a minimum and maximum gaming game participated by two players, and the task of one player (generator, generator) is to map random input into data conforming to a certain specific distribution, so that the second player (discriminator, Disscriminator