Tamas Ungi

Tamas Ungi is a Research Associate and Adjunct Assistant Professor at Queen's University, focusing on medical imaging, computer-assisted surgery, and biomedical engineering. His work bridges artificial intelligence applications with clinical needs in oncology, urology, and surgical education.

• Queen's University

His research interests center on:

• 3D ultrasound imaging
• Surgical navigation systems
• Machine learning for medical diagnostics
• Tumor margin assessment
• Surgical skill evaluation
• Image-guided interventions

Recent publications highlight advancements in radiation-free pediatric scoliosis assessment, AI-driven surgical evaluation metrics, and real-time ultrasound segmentation for breast-conserving surgery. He also explores electromagnetic tracking systems and NURBS-based surgical planning tools.