Brain tumor segmentation by combining MRI multimodal information and improved Unet network

Brain tumor is one of the common diseases of nervous system. Because of the different size and location of each tumor region in the brain tumor image, the traditional brain tumor image segmentation method has poor segmentation effect at the edge of each tumor region. In recent years, deep learning has been applied to medical image segmentation this paper proposes an improved attentional Unet model. Firstly, the complex 3D brain tumour image segmentation is decomposed into simpler 2D segmentation tasks. Secondly, the network model is tested and compared with the segmentation results of the classical segmentation network, the network in this paper has a good segmentation effect.