CT image segmentation system based on attention convolutional neural network

The invention provides a CT image segmentation system based on an attention convolutional neural network, and the system comprises a feature coding module which uses a parallel convolutional neural network to gradually reduce the size of a feature map of an input image, and achieves the simultaneous extraction of image semantic information and spatial information through the multiplexing of a network layer and the interception and fusion of features of all layers; the semantic information extraction attention module which is used for generating attention features by pooling and further refining the semantic information features extracted by the feature coding module; the feature fusion pooling attention module which is used for fusing the refined semantic information features with the semantic information and spatial information features spliced by the feature coding module to form an attention feature map by using parallel connection of maximum pooling and average pooling; and the feature map decoding module