Medical-DCGAN
Zakaria Rguibi, Hajami Abedlamjid, Dya Zitouni, Amine Elqaraoui · 2024
Deep learning is a powerful tool for medical image analysis. It can be used to detect and diagnose diseases, as well as to predict the outcomes of treatments. Deep convolutional generative adversarial networks (DCGANs) have achieved promising results in various domains of image generation. However, their research status in medical images is still unclear. In this chapter, we investigate the research status of DCGANs in medical images by comparing their performance with other state-of-the-art methods on challenging tasks in medical image classification. Our experimental results show that Medical-DCGAN achieves great results in terms of quality image and computational resource. The study addresses both their applications in medical imaging and adversarial learning for medical imaging. The open challenges and future research directions are also discussed.