Longitudinal MRI

Longitudinal MRI studies analyze repeated scans of the same individual over time, aiming to track changes in brain structure and function for various conditions like Alzheimer's disease and multiple sclerosis. Current research emphasizes the development of deep learning models, including transformers and diffusion models, to improve the accuracy and efficiency of analyzing longitudinal data, often focusing on tasks such as lesion segmentation, cortical reconstruction, and atrophy prediction. These advancements are crucial for improving disease monitoring, treatment efficacy assessment, and ultimately, personalized medicine by providing more precise and timely insights into disease progression.