Glioma is one of the most lethal tumors in the world. It is a malignant disease with high mortality, easy recurrence, and great harm to the body. At present, magnetic resonance imaging (MRI) technology, due to its characteristics of clear imaging effect and sharp contrast between different soft tissues, has become a commonly used medical method to diagnose patients with glioma. Given the lack of original glioma data set, this study, in cooperation with Liaoning Tumor Hospital, analyzed MRI images of 300 glioma patients in the hospital. The original glioma data set is established by classifying and further grading the original data through lesion determination, lesion location, and lesion qualitative. Analysis and experiment are conducted to verify its subsequent application. It is proved that the original data set can be used for image classification and segmentation, providing image data for tumor growth and reconstruction and sufficient help for clinical research and application of glioma.