Deformable 3D-2D registration of known components for image guidance in spine surgery

A. Uneri, J. Goerres, T. De Silva, M. W. Jacobson, M. D. Ketcha, S. Reaungamornrat, G. Kleinszig, S. Vogt, A. J. Khanna, J. P. Wolinsky, J. H. Siewerdsen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

A 3D-2D image registration method is reported for guiding the placement of surgical devices (e.g.,K-wires). The solution registers preoperative CT (and planning data therein) to intraoperative radiographs and computes the pose,shape,and deformation parameters of devices (termed “components”) known to be in the radiographic scene. The deformable known-component registration (dKC-Reg) method was applied in experiments emulating spine surgery to register devices (K-wires and spinal fixation rods) undergoing realistic deformation. A two-stage registration process (i) resolves patient pose from individual radiographs and (ii) registers components represented as polygonal meshes based on a B-spline model. The registration result can be visualized as overlay of the component in CT analogous to surgical navigation but without conventional trackers or fiducials. Target registration error in the tip and orientation of deformable K-wires was (1.5 ± 0.9) mm and (0.6° ± 0.2°),respectively. For spinal fixation rods,the registered components achieved Hausdorff distance of 3.4 mm. Future work includes testing in cadaver and clinical data and extension to more generalized deformation and component models.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
EditorsLeo Joskowicz, Mert R. Sabuncu, William Wells, Gozde Unal, Sebastian Ourselin
PublisherSpringer Verlag
Pages124-132
Number of pages9
ISBN (Print)9783319467252
DOIs
StatePublished - 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9902 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Funding

Research supported by NIH grant R01-EB-017226 and academic-industry partnership with Siemens Healthcare (XP Division, Erlangen Germany).

Keywords

  • 3D-2D registration
  • Deformable registration
  • Image-guided surgery
  • Quality assurance
  • Spine surgery
  • Surgical navigation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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