The invention provides an MRI (Magnetic Resonance Imaging) segmentation method for integrating an attention mechanism aiming at brain lesions. The method comprises the following steps: S1, collecting a brain MRI image with a segmentation image result, and establishing a training set; s2, preprocessing the original brain MRI image to be segmented in the training set; s3, establishing a convolutional neural network with an attention mechanism, and training a model of the convolutional neural network by using the training set; s4, after model training is completed, using trained model parameters to predict the verification set image, and generating a brain MRI tissue and lesion segmentation map; s5, establishing an evaluation file, and evaluating a segmentation result; according to the method, more critical and important information can be extracted, and meanwhile, the training effect of training on a small data set is improved by means of transfer learning.