Cortical Surface Diffusion Generative Models

Cortical surface analysis has gained increased prominence, given its potential implications for neurological and developmental disorders. Traditional vision diffusion models, while effective in generating natural images, present limitations in capturing intricate development patterns in neuroimaging due to limited datasets. This is particularly true for generating cortical surfaces where individual variability in cortical morphology is high, leading to an urgent need for better methods to model brain development and diverse variability inherent across different individuals. In this work, we proposed a …

analysis cs.cv datasets development diffusion diffusion models eess.iv generative generative models images limitations natural neuroimaging patterns surface true vision