3D reconstruction of cardiac volume with C-arm CT allows surgeons to perform intra-operative planning of the intervention. To treat stenosed coronary arteries (which is the most frequent coronary artery disease) it is necessary to provide surgeon with such characteristics as vessel tree topology, spacial orientation of stenosed vessel segment, lumen diameter, tortuosity, vessel calcification, etc. Manual measurement of these parameters is tedious, error-prone and not accurate.

 

This research project is focused on the segmentation of coronary vessel tree in C-arm CT data and providing quantitative 3D measurements of vessel geometry. The project is supported by Siemens Healthcare, Forchheim and the Chair of Pattern Recognition.