title: Planning and intraoperative visualization of liver catheterizations: new CTA protocol and 2D-3D registration method.
abstract: OBJECTIVE
  Two-dimensional and three-dimensional (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, in spite of a valuable body of research results in the neuroradiology community, an adequate registration algorithm that addresses the difficult task of 2D-3D alignment of abdominal vessel structures has not been developed yet.
  
  
  METHODS
  We address the first issue by introducing an angiographic computed tomography (CT) scanning phase. The scan visualizes arteries similar to the vasculature captured with an intraoperative C-arm acquiring digitally subtracted angiograms. Furthermore, we propose a registration algorithm using the new CT phase that aligns arterial structures in two steps: 1) Initialization of one corresponding feature using diameter information and 2) optimization on three rotational and one translational parameters 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.
  
  
  RESULTS
  We show convergence and robustness of the proposed algorithm on synthetic data, as well as head phantom and four consistent patient data sets. We compare our results with those of a recently proposed method. Moreover, we evaluate different visualization techniques and show that a transfer of planning information to intraoperative data is a benefit for interventional workflow.
  
  
  CONCLUSIONS
  Introducing a new CTA protocol and a two-step 2D-3D registration algorithm, the proposed method creates a strong link between radiologists and interventionalists by bringing preoperative patient and planning information to interventional workflow.
authors.affiliation: Chair for Computer Aided Medical Procedures (CAMP), TU München, Boltzmannstr. 3, 85748 Garching b. München, Germany. groher@cs.tum.edu
authors.forename: Martin
authors.initials: M
authors.lastname: Groher
authors.forename: Tobias F
authors.initials: TF
authors.lastname: Jakobs
authors.forename: Nicolas
authors.initials: N
authors.lastname: Padoy
authors.forename: Nassir
authors.initials: N
authors.lastname: Navab
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D002404:Catheterization / Q000379:methods*; D003196:Computer Graphics; D006499:Hepatic Artery / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D011300:Preoperative Care / 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; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014584:User-Computer Interface