title: Continuous roadmapping in liver TACE procedures using 2D-3D catheter-based registration.
abstract: OBJECTIVE
  Fusion of pre/perioperative images and intra-operative images may add relevant information during image-guided procedures. In abdominal procedures, respiratory motion changes the position of organs, and thus accurate image guidance requires a continuous update of the spatial alignment of the (pre/perioperative) information with the organ position during the intervention.
  
  
  METHODS
  In this paper, we propose a method to register in real time perioperative 3D rotational angiography images (3DRA) to intra-operative single-plane 2D fluoroscopic images for improved guidance in TACE interventions. The method uses the shape of 3D vessels extracted from the 3DRA and the 2D catheter shape extracted from fluoroscopy. First, the appropriate 3D vessel is selected from the complete vascular tree using a shape similarity metric. Subsequently, the catheter is registered to this vessel, and the 3DRA is visualized based on the registration results. The method is evaluated on simulated data and clinical data.
  
  
  RESULTS
  The first selected vessel, ranked with the shape similarity metric, is used more than 39 % in the final registration and the second more than 21 %. The median of the closest corresponding points distance between 2D angiography vessels and projected 3D vessels is 4.7-5.4 mm when using the brute force optimizer and 5.2-6.6 mm when using the Powell optimizer.
  
  
  CONCLUSIONS
  We present a catheter-based registration method to continuously fuse a 3DRA roadmap arterial tree onto 2D fluoroscopic images with an efficient shape similarity.
authors.affiliation: Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam, The Netherlands, p.ambrosini@erasmusmc.nl.
authors.forename: Pierre
authors.initials: P
authors.lastname: Ambrosini
authors.forename: Daniel
authors.initials: D
authors.lastname: Ruijters
authors.forename: Wiro J
authors.initials: WJ
authors.lastname: Niessen
authors.forename: Adriaan
authors.initials: A
authors.lastname: Moelker
authors.forename: Theo
authors.initials: T
authors.lastname: van Walsum
mesh_terms: D000465:Algorithms; D000792:Angiography; D001331:Automation; D006528:Carcinoma, Hepatocellular / Q000628:therapy; D002404:Catheterization; D057785:Catheters; D016461:Chemoembolization, Therapeutic / Q000295:instrumentation* / Q000379:methods; D003198:Computer Simulation; D003287:Contrast Media / Q000737:chemistry; D005471:Fluoroscopy / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008113:Liver Neoplasms / Q000628:therapy; D015233:Models, Statistical; D009038:Motion; D012119:Respiration; D012189:Retrospective Studies
chemical_list: D003287:Contrast Media