Rib Fracture

Rib fractures, a common and clinically significant injury, are challenging to reliably detect in medical imaging. Current research focuses on developing and improving deep learning models, particularly object detection networks, for automated rib fracture identification and classification from chest CT scans and X-rays. These models leverage various forms of supervision, including fully labeled, weakly labeled, and unlabeled data, to improve accuracy and reduce the need for extensive manual annotation by radiologists. Improved automated detection promises faster and more consistent diagnosis, ultimately leading to better patient care and potentially reducing healthcare costs.