FracFormer: Semi-supervised Learning for Vertebrae and Fracture Classification on 3D Radiographs with Transformers

This repository is the official implementation of FracFormer: Semi-supervised Learning for Vertebrae and Fracture Classification on 3D Radiographs with Transformers. Our framework applies transformer-based models to detect vertebrae fractures, incorporating a Vision Transformer for spine detection and a Swin Transformer for fracture identification. This approach leverages the strengths of transformers in medical imaging to advance vertebral and fracture classification accuracy on 3D radiographic data.

Work in Progress 🚧

This repository is currently under active development, with regular updates expected.