MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery

S. Reaungamornrat, T. De Silva, A. Uneri, J. P. Wolinsky, A. J. Khanna, G. Kleinszig, S. Vogt, J. L. Prince, J. H. Siewerdsen

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

3 Scopus citations

Abstract

Purpose: Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method: The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result: The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions: A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration accuracy suitable to application in image-guided spine surgery across a broad range of anatomical sites and modes of deformation.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2016
Subtitle of host publicationImage-Guided Procedures, Robotic Interventions, and Modeling
EditorsRobert J. Webster, Ziv R. Yaniv
PublisherSPIE
ISBN (Electronic)9781510600218
DOIs
StatePublished - 2016
EventMedical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling - San Diego, United States
Duration: Feb 28 2016Mar 1 2016

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9786
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling
CountryUnited States
CitySan Diego
Period2/28/163/1/16

Keywords

  • CT
  • Demons algorithm
  • MIND
  • MRI
  • deformable image registration
  • image-guided surgery
  • multimodality image registration
  • symmetric diffeomorphism

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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