Generation and Evaluation of Medical Images Based on Diffusion Models

Within the framework of evolving intelligent systems, the work on generating and evaluating synthetic medical images using diffusion models represents a significant step towards overcoming the challenge of data scarcity, a critical obstacle in current medical research. In this paper, a system for generating and evaluating synthetic medical images using diffusion models is presented. It addresses the challenge of insufficient public medical datasets, proposing artificial intelligence models to generate synthetic medical data. This aims to overcome current research limitations due to data scarcity. The research of this paper includes the development of a system architecture and a proof of concept, assessing the feasibility of using synthetic images in healthcare.