A deep learning solution to generate artificial MRI images of different contrast levels from existing MRI scans. This will help to provide a better diagnosis with the help of an additional image.
Developing a CycleGAN model to translate the style of one MRI image to another, which will help in a better understanding of the scanned image. Using this solution we can create T2 weighted images from T1 weighted MRI image and vice-versa.