Advanced 3D MRI analysis powered by SFCN neural networks. Upload a brain scan and get AI-powered age prediction, volumetric analysis, and clinical insights in minutes.
Interactive NiiVue rendering with Three.js mesh overlays. Explore brain regions in full 3D with severity heatmaps and region highlighting.
SFCN dual-branch model (3D CNN + tabular MLP) predicts brain age from T1-weighted MRI. Trained on 6,050 healthy subjects across 12 datasets.
LLM-generated explanations for each scan. Per-region z-scores, cognitive domain mapping, and downloadable PDF reports with clinical narratives.
Upload a T1-weighted NIfTI brain scan through the secure web interface.
Preprocessing, skull-stripping, MNI registration, and atlas-based segmentation.
SFCN model predicts brain age. Brain age gap computed against chronological age.
AI generates region-by-region analysis, z-scores, cognitive mapping, and PDF report.
BrainAge AI — Built with PyTorch, FastAPI, and Groq LLM
Model: bilalEthizo/BrainAge-SFCN • 6,050 subjects • 12 datasets