Brain MRI

Brain MRI research develops methods to measure brain anatomy and detect or characterize conditions such as tumors, multiple sclerosis, stroke, and neurodegeneration. Common approaches include U-Net-style segmentation, transformer and graph models, multimodal learning, and self-supervised foundation models, evaluated on datasets such as BraTS, ADNI, and IBSR. Other work reconstructs or enhances images, estimates biomarkers such as brain age, and uses language models to analyze scans and reports. A central challenge is ensuring that results generalize across scanners, sites, and patient groups while preserving clinically important details and demonstrating value beyond image-similarity scores or benchmark accuracy.