The method is applied to the technical field of artificial intelligence, relates to the technical field of blockchain, and discloses a brain tumor image segmentation method, device and equipment basedon deep learning, and a medium. The method includes, in part, the following steps: obtaining a multi-mode brain nuclear magnetic resonance image; preprocessing the brain nuclear magnetic resonance image, so as to obtain a target image with the skull part being removed; and finally, inputting the target image into a preset brain tumor segmentation model, so as to obtain a brain tumor image segmentation result, wherein the preset brain glioma segmentation model is a deep learning model obtained by performing cross validation training according to an adaptive segmentation framework and a brain nuclear magnetic resonance image without a skull part, and the adaptive segmentation framework comprises a plurality of different types of U-Net models and U-Net integrated models. According to the invention, the optimal network structure for prediction in the plurality of models can be automatically selected according to the result of cross validation, and the segmentation performance of the preset brain tumor segmentation model is improved, so the accuracy of brain tumor image segmentation is improved.