Aiming at the problem of misrecognition of magnetic resonance imaging (MRI) brain tumor regions and large differences in tumor shape,a MRI brain tumor image segmentation method b ased on multi-scale feature extraction is proposed.The segmentation model uses U-Net as the backbone network and uses dense pyramid convolution (DPC) to extra c t multi-scale features to adapt to the segmentation of tumors of different size s .At the same time,it introduces strip pooling (SP),which can capture the long -distance area of the tumor.Dependency,further strengthen the segmentation ab i lity of tumor images.The proposed method has been experimentally verified on th e Kaggle_3m data set.The experimental results show that the method has good bra in tumor segmentation performance.The Dice similarity coefficient and the Jacca rd coefficient have reached 91.66% and 84.38%,respectively.