Generative AI in MS Neuroimaging

This lecture surveyed how generative models may help MS neuroimaging, from synthetic contrasts and privacy-preserving data to radiology reports. The same deck was used for an IPMSA session later in 2025.

The question

Can a model that learns the distribution of MRI data extend what researchers can study without introducing new error or bias?

Deck outline

• The distinction between discriminative and generative models
• Synthetic MRI contrasts and enrichment of clinical scans
• Synthetic data as a route to greater privacy
• Generative models for treatment-effect research
• Bias, fairness and equitable model performance
• Small samples, limited validation and the gap to clinical impact

Take-away

Generative AI is versatile, but clinical value still depends on external validation, meaningful outcomes and careful assessment of fairness.