Prostate Cancer diagnosis by Generative Adversarial Networks: Generating High-Fidelity Synthetic Magnetic Resonance Images

Abstract

Prostate cancer is a significant health issue for men, it requires early detection for effective treatment. MRI is essential for diagnosis, but low-resolution images can lead to errors. In this project, we used Generative Adversarial Networks (GANs) to enhance MRI quality and deep learning (DL) for accurate analysis of medical images. By integrating GANs and DL, we create a platform that improves MRI resolution and diagnostic accuracy, aiding doctors in effective prostate cancer detection. As a result, we achieved significant improvements in the diagnostic process, contributing to more reliable identification of prostate cancer.