The invention discloses a neural network, a magnetic resonance brain tissue segmentation method and device based on the neural network, computing equipment and a storage medium. The neural network canbe a convolutional neural network, comprises at least one three-dimensional (3D) asymmetric convolution module or a convolutional neural network, and comprises at least one encoder, a bottleneck layer and a decoder which are coupled in sequence, and the at least one 3D asymmetric convolution module is located in at least one of the encoder, the bottleneck layer and the decoder; the 3D asymmetricconvolution module comprises a 3D standard convolution layer and three 3D asymmetric convolution layers corresponding to the 3D standard convolution layer, and the four formed convolution layers are used for carrying out convolution operation on data input into the 3D asymmetric convolution module, sum operation is carried out on convolution operation results and then the convolution operation results are output. By using the method, the brain tissue segmentation precision of the brain MRI image data can be improved.
Magnetic resonance brain tissue segmentation method and device based on neural network, computing equipment and storage medium