About AI in Radiology
Our research explores AI-driven imaging analysis, enabling faster and more accurate medical diagnoses. We develop algorithms that enhance MRI, CT, and X-ray interpretation across oncology, neurology, and cardiology.
Key contributions include:
- Deep learning models for tumor detection with >97% accuracy
- Automated image segmentation and anomaly detection tools
- AI-assisted radiologist workstations for real-time analysis
Current Research Projects
Neural Radiology Analysis
AI models that identify pathologies in MRI and CT scans with sub-millimeter precision.
Lead: Dr. Emily Zhang
View Project →3D X-ray Reconstruction
AI-driven conversion of 2D radiographs into detailed 3D anatomical models for surgical planning.
Lead: Dr. David Lin
Learn More →Join the AI Radiology Innovation Network
Collaborate with clinical experts and AI developers to transform diagnostic imaging technologies.
Initiate PartnershipRelated Publications
Tumor Segmentation Algorithms (2024)
Chest X-ray Anomaly Detection
3D Reconstruction Toolkit