Endometrial cancer is the most common gynecological malignant tumor in developed countries, and accurate preoperative risk stratification is essential for personalized medicine. For realizing tumor feature extraction by radiomics approach, the segmentation of the tumor is usually required. The model developed in this study has achieved high-accuracy automatic segmentation of endometrial cancer on MRI using a convolutional neural network for the first time. Using multi-sequence MR images were important for high accuracy segmentation. Our model will lead to efficient medical image analysis of a large number of cases using the radiomics approach and/or deep learning methods.