At present, mixed reality (MR) technology is gaining increasingly attention in digital medicine. Targeted at MR of glioma medical image analysis, this study proposes an MR glioma location and regional segmentation algorithm based on the 3D UNet deep learning model, and uses the surface rendering method to render and optimize multi-structure tissue of the glioma image in three-dimensional space. On this basis, three-dimensional registration tracking and visual space sharing algorithms are presented using the interactive markerless and the marker-based graphs for mobile MR to achieve the real-time third-view space sharing for MR multi-devices. In addition, an MR experimental system is designed and implemented for glioma medical image analysis. The experimental results show that the methods proposed in this paper can effectively realize the detection, segmentation and three-dimensional reconstruction of the brain glioma. Through the real-time sharing of mobile MR devices, the proposed methods can effectively achieve MR analysis of glioma medical images to support the auxiliary diagnosis and treatment of glioma, and it also can provide new methods for preoperative planning, medical education and training, etc.