CT Image-Based FE Modeling for Femoral Lesion Assessment

This project develops an automated modeling framework to predict femoral fracture risk in patients with lytic bone lesions. The approach integrates patient-specific imaging data with computational modeling to estimate structural weakening and mechanical failure risk. By streamlining model generation and analysis, the framework aims to support more consistent, scalable, and clinically actionable fracture risk assessment.

Intern: Brandon Jeon

Mentor: Jiangyue Zhang (REDD)