Medical radiologist diagnoses a medical condition from several varieties of medical image, e.g. MRI images or CT images. Since it is predicted that patients will increase along with the elderly society in Japan, the researches for classifying the abnormal images based on the Deep Learning technique has increased to prevent diagnosis mistakes. Furthermore, there is an increasing need to perform mutual transformation from certain medical images to other modality of images, e.g., from MRI images to CT images. Because different modality of images are taken independently, the patient load becomes big issue to take some medical inspections.

Therefore, in this study, we try to transform from the certain MRI image to the other type of MRI image by using the CycleGAN algorithm known as one of Deep Learning methods. There are two variation of MRI images, i.e., normal weighted images and fat-suppressed weighted images.