Fracture detection in hand radiographs

Scaphoid fractures are the most common fractures of the carpal bones. They may be difficult to detect in the acute phase. The consequences of missing a fracture can be severe, with complications such as avascular necrosis, carpal instability, osteoarthritis, surgical intervention for bony repositioning and fixation or resection of the proximal carpal row, and ultimately functional loss. Due to the risks involved, more than half of the patients receive unnecessary wrist immobilization out of precaution, increasing health expenditure. In this project we therefore develop deep learning detection systems for diagnosing scaphoid fractures on radiographs. In the future, we plan to create an AI system that can provide a comprehensive report of hand radiographs acquired at the emergency ward.

Funding

People

Nils Hendrix

Nils Hendrix

PhD Candidate

Matthieu Rutten

Matthieu Rutten

Associate Professor, Radiologist

Eric Postma

Eric Postma

Professor

Artificial Intelligence, Tilburg University

Bram van Ginneken

Bram van Ginneken

Professor, Scientific Co-Director