FURI | Spring 2024

Understanding Neuroinflammation in Neurodegenerative Diseases using a Contrastive Learning Approach on MRSI Data

The research team proposes a novel approach to understand neuroinflammation in neurodegenerative diseases using high-resolution MRSI data and machine learning techniques. Leveraging Contrastive Principal Component Analysis (CPCA), they aim to derive latent representations of basal and lesioned MRSI in mice. By adapting methods from human data analysis, they seek to explore neuroimmune states and pathology. This project aligns with health and data research themes, offering potential clinical applications for early diagnosis and treatment of neuroinflammation in neurodegenerative diseases.