Two-dimensional roadmapping is considered state-of-the-art in guidewire navigation during endovascular interventions.
This paper presents a methodology for extracting the guidewire from a sequence of 2-D roadmap
images in almost real time. The detected guidewire can be used to improve its visibility on noisy fluoroscopic
images or to do a back projection of the guidewire into a registered 3-D vessel tree. A lineness filter based on
the Hessian matrix is used to detect only those line structures in the image that lie within the vessel tree. Loose
wire fragments are properly linked by a novel connection method fulfilling clinical processing requirements. We
show that Dijkstra's algorithm can be applied to efficiently compute the optimal connection path. The entire
guidewire is finally approximated by a B-spline curve in a least-squares manner. The proposed method is both
integrated into a commercial clinical prototype and evaluated on five different patient data sets containing up to
249 frames per image series.