title: New CTA protocol and 2D-3D registration method for liver catheterization.
abstract: 2D-3D registration for angiographic liver interventions is an unsolved problem mainly because of two reasons. First, a suitable protocol for Computed Tomography Angiography (CTA) to contrast liver arteries is not used in clinical practice. Second, an adequate registration algorithm which addresses the difficult task of aligning deformed vessel structures has not been developed yet. We address the first issue by introducing an angiographic CT scanning phase and thus create a strong link between radiologists and interventionalists. The scan visualizes arteries similar to the vasculature captured with an intraoperative C-arm acquiring Digitally Subtracted Angiograms (DSAs). Furthermore, we propose a registration algorithm using the new CT phase that aligns arterial structures in two steps: (a) Initialization of one corresponding feature using vessel diameter information, (b) optimization on three rotational and one translational parameter to register vessel structures that are represented as centerline graphs. We form a space of good features by iteratively creating new graphs from projected centerline images and by restricting the correspondence search only on branching points (the vertices) of the vessel tree. This algorithm shows good convergence and proves to be robust against deformation changes, which is demonstrated through studies on one phantom and three patients.
authors.affiliation: Technische Universität München, Germany. groher@cs.tum.edu
authors.forename: Martin
authors.initials: M
authors.lastname: Groher
authors.forename: Nicolas
authors.initials: N
authors.lastname: Padoy
authors.forename: Tobias E
authors.initials: TE
authors.lastname: Jakobs
authors.forename: Nassir
authors.initials: N
authors.lastname: Navab
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D001185:Artificial Intelligence; D002404:Catheterization / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008099:Liver / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015641:Radiography, Interventional / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*