Medical Image Generation

Medical image generation uses artificial intelligence to create realistic synthetic medical images, primarily aiming to address data scarcity and privacy concerns in healthcare. Current research focuses on leveraging diffusion models, often incorporating additional controls like radiomic features or expert gaze patterns, to improve image realism and anatomical accuracy. These advancements are significant because they enable the creation of large, diverse datasets for training deep learning models, facilitating improved diagnostic tools and accelerating medical research while mitigating patient privacy risks. Furthermore, generated images are proving useful in medical education and simulation.