Brain Tumour Segmentation Using Wasserstein Generative Adversarial Networks(WGANs)

The majority of health-related applications use technology and require a lot of data to operate. Even more, information is required for brain tumor segmentation, but many people lack access to it because of privacy laws governing medical information. Therefore, this study utilizes GAN technology, which creates synthetic images to resolve this issue. AGGrGAN is used for aggregation and discrimination, and PGAN, WGAN, and DCGAN are used to create synthetic pictures. Synthetic brain tumor masks with the same visual characteristics as the real samples. potential benefits of using GANs to synthesize new images from a real dataset of brain MR scans and corresponding hand-labelled segmentation masks (annotations), and an evaluation of the potential performance gains that are achieved when using synthetic images to augment a dataset that is used to train a neural network to solve a brain tumour segmentation task.