A brain tissue layering method and device based on a neural network, a computer device, and a storage medium, relating to the field of artificial intelligence. The method comprises: obtaining brain CT image information (201); extracting features of the brain CT image information by means of a pre-trained brain cutting convolutional neural network to obtain a feature map of the brain CT image (202); performing a candidate box alignment operation on the feature map of the brain CT image to obtain semantic information of an instance category and location information of an instance pixel level (203); and inputting the semantic information of the instance category and the location information of the instance pixel level into a pre-trained layering neural network, and outputting a layered result of the brain CT image (204). By fusing the brain cutting convolutional neural network and the brain layering neural network, the results of brain cutting and brain layering are obtained simultaneously by using one model, so that the operation time and the consumption of operation resources are reduced, and the tasks of brain cutting and brain layering can share feature information, thereby improving the accuracy of brain layering.
BRAIN TISSUE LAYERING METHOD AND DEVICE BASED ON NEURAL NETWORK, AND COMPUTER DEVICE