Longitudinal Brain MRI

Longitudinal brain MRI studies analyze repeated scans of the same individual over time, aiming to track brain changes related to disease progression, development, or treatment response. Current research focuses on improving the accuracy and interpretability of deep learning models, particularly convolutional neural networks, for analyzing these complex datasets, addressing challenges like data leakage and developing self-supervised learning approaches for registration and representation learning. These advancements are crucial for improving diagnostic accuracy, monitoring disease trajectories, and personalizing treatment strategies in various neurological conditions.