Objectives: In the Netherlands, cyclists continue to outnumber other road users in injuries and deaths. The wearing of bicycle helmets is not mandatory in the Netherlands even though research has shown that wearing bicycle helmets can reduce head and brain injuries by up to 88%. Therefore, the aim of this study was to assess the feasibility of using 3D technology to evaluate bicycle-related head injuries and helmet protection. Methods: Three patients who had been involved in a bicycle accident while wearing a helmet were subjected to multi-detector row computed tomography (MDCT) imaging after trauma. The helmets were separately scanned using the same MDCT scanner with tube voltages ranging from 80. kVp to 140. kVp and tube currents ranging from 10. mAs to 300. mAs in order to determine the best image acquisition parameters for helmets. The acquired helmet images were converted into virtual 3D surface hence Standard Tessellation Language (STL) models and merged with MDCT-derived STL models of the patients' skulls. Finally, all skull fractures and corresponding helmet damage were visualized and related. Results: Imaging bicycle helmets on an MDCT scanner proved to be feasible using a tube voltage of 120. kVp and a tube current of 120. mAs. Merging the resulting STL models of the patients' skull and helmet allowed the overall damage sustained by both skull and helmet to be related. Conclusion: Our proposed 3D method of assessing bicycle helmet damage and corresponding head injuries could offer valuable information for the development and design of safer bicycle helmets.