Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images.

Journal: International journal of computer assisted radiology and surgery
Published Date:

Abstract

PURPOSE: The registration of a 3D atlas image to 2D radiographs enables 3D pre-operative planning without the need to acquire costly and high-dose CT-scans. Recently, many deep-learning-based 2D/3D registration methods have been proposed which tackle the problem as a reconstruction by regressing the 3D image immediately from the radiographs, rather than registering an atlas image. Consequently, they are less constrained against unfeasible reconstructions and have no possibility to warp auxiliary data. Finally, they are, by construction, limited to orthogonal projections.

Authors

  • Jeroen Van Houtte
    imec-Visionlab, University of Antwerp, 2610, Antwerp, Belgium. jeroen.vanhoutte@uantwerpen.be.
  • Emmanuel Audenaert
    Department Human Structure and Repair, University Ghent, 9000, Ghent, Belgium.
  • Guoyan Zheng
    Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland. guoyan.zheng@istb.unibe.ch.
  • Jan Sijbers
    Imec-Vision Lab, Department of Physics, University of Antwerp, B-2610, Antwerp, Belgium.