Style Transfer Using Generative Adversarial Networks for Brain MRI Enhancement

Using a specific Generative Adversarial Model known as CycleGAN, the purpose of this research is to provide a method for the generation of synthetic MRI (Magnetic Resonance Imaging) images. Using a GAN, this model will assist us in the creation of a Super resolution picture of an MRI. This will be accomplished by changing and balancing the contract for the original MRI image, which will ensure that the medical industry operates at a high level of efficiency. Increasing the quality of the original MRI scans is the key objective, which will be accomplished by the effective representation of MRI scans by GANs.