Linear programming approach to optimize 3D data obtained from multiple view angiograms

Three-dimensional (3D) vessel data from CTA or MRA are not always available prior to or during endovascular interventional procedures, whereas multiple 2D projection angiograms often are. Unfortunately, patient movement, table movement, and gantry sag during angiographic procedures can lead to large errors in gantry-based imaging geometries and thereby incorrect 3D. Therefore, we are developing methods for combining vessel data from multiple 2D angiographic views obtained during interventional procedures to provide 3D vessel data during these procedures. Multiple 2D projection views of carotid vessels are obtained, and the vessel centerlines are indicated. For each pair of views, endpoints of the 3D centerlines are reconstructed using triangulation based on the provided gantry geometry. Previous investigations indicated that translation errors were the primary source of error in the reconstructed 3D. Therefore, the errors in the translations relating the imaging systems are corrected by minimizing the L1 distance between the reconstructed endpoints, after which the 3D centerlines are reconstructed using epipolar constraints for every pair of views. Evaluations were performed using simulations, phantom data, and clinical cases. In simulation and phantom studies, the RMS error decreased from 6.0 mm obtained with biplane approaches to 0.5 mm with our technique. Centerlines in clinical cases are smoother and more consistent than those calculated from individual biplane pairs. The 3D centerlines are calculated in about 2 seconds. These results indicate that reliable 3D vessel data can be generated for treatment planning or revision during interventional procedures.