• DocumentCode
    1057367
  • Title

    Deformable 2D-3D Registration of Vascular Structures in a One View Scenario

  • Author

    Groher, Martin ; Zikic, Darko ; Navab, Nassir

  • Author_Institution
    Comput. Aided Med. Procedures & Augmented Reality, Tech. Univ. Munchen, Munich
  • Volume
    28
  • Issue
    6
  • fYear
    2009
  • fDate
    6/1/2009 12:00:00 AM
  • Firstpage
    847
  • Lastpage
    860
  • Abstract
    Alignment of angiographic 3D scans to 2D projections is an important issue for 3D depth perception and navigation during interventions. Currently, in a setting where only one 2D projection is available, methods employing a rigid transformation model present the state of the art for this problem. In this work, we introduce a method capable of deformably registering 3D vessel structures to a respective single projection of the scene. Our approach addresses the inherent ill-posedness of the problem by incorporating a priori knowledge about the vessel structures into the formulation. We minimize the distance between the 2D points and corresponding projected 3D points together with regularization terms encoding the properties of length preservation of vessel structures and smoothness of deformation. We demonstrate the performance and accuracy of the proposed method by quantitative tests on synthetic examples as well as real angiographic scenes.
  • Keywords
    biomechanics; blood vessels; deformation; diagnostic radiography; image registration; medical image processing; 2D projection; 3D depth perception; 3D vessel structure registration; angiographic 3D scan; deformable 2D-3D registration; digitally subtracted angiogram; quantitative test; rigid transformation model; vascular structure; Abdomen; Angiography; Augmented reality; Biomedical imaging; Catheters; Encoding; Layout; Medical diagnostic imaging; Navigation; Visualization; 2D-3D registration; Angiography; deformable registration; Algorithms; Angiography; Artificial Intelligence; Blood Vessels; Carcinoma, Hepatocellular; Humans; Image Processing, Computer-Assisted; Liver; Models, Cardiovascular; Models, Statistical;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2008.2011519
  • Filename
    4738333