Longitudinal Brain

Longitudinal brain studies analyze brain changes over time, primarily using MRI scans, to understand brain development, aging, and disease progression. Current research focuses on developing sophisticated deep learning models, including diffusion-based generative models and graph neural networks, to accurately predict and simulate brain changes from limited data, addressing challenges like data scarcity and data leakage. These advancements improve the analysis of longitudinal brain data, enabling more precise tracking of disease progression and potentially leading to improved diagnostics and personalized treatment strategies. The development of robust and reliable methods for analyzing longitudinal brain data is crucial for advancing our understanding of brain health and disease.