Synthesizing CTA Image Data for Type-B Aortic Dissection using Stable Diffusion Models

Understand

Stable Diffusion (SD) has gained a lot of attention in recent years in the field of Generative AI thus helping in synthesizing medical imaging data with distinct features.

• The aim is to contribute to the ongoing effort focused on overcoming the limitations of data scarcity and improving the capabilities of ML algorithms for cardiovascular image processing.
• Therefore, in this study, the possibility of generating synthetic cardiac CTA images was explored by fine-tuning stable diffusion models based on user defined text prompts, using only limited number of CTA images as input.
• A comprehensive evaluation of the synthetic data was conducted by incorporating both quantitative analysis and qualitative assessment, where a clinician assessed the quality of the generated data.