Synthetic Brain Images: Bridging the Gap in Brain Mapping With Generative Adversarial Model

arXiv:2404.08703v1 Announce Type: cross
Abstract: Magnetic Resonance Imaging (MRI) is a vital modality for gaining precise anatomical information, and it plays a significant role in medical imaging for diagnosis and therapy planning. Image synthesis problems have seen a revolution in recent years due to the introduction of deep learning techniques, specifically Generative Adversarial Networks (GANs). This work investigates the use of Deep Convolutional Generative Adversarial Networks (DCGAN) for producing high-fidelity and realistic MRI image slices. The suggested approach uses a …

abstract adversarial arxiv brain brain mapping cs.cv diagnosis eess.iv gap generative image images imaging information introduction mapping medical medical imaging mri planning q-bio.nc role synthesis synthetic therapy type vital