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 language | English (US) |
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Title of host publication | Medical Imaging 2016 |
Subtitle of host publication | Image-Guided Procedures, Robotic Interventions, and Modeling |
Editors | Robert J. Webster, Ziv R. Yaniv |
Publisher | SPIE |
ISBN (Electronic) | 9781510600218 |
DOIs | |
State | Published - 2016 |
Event | Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling - San Diego, United States Duration: Feb 28 2016 → Mar 1 2016 |
Publication series
Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
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Volume | 9786 |
ISSN (Print) | 1605-7422 |
Other
Other | Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling |
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Country/Territory | United States |
City | San Diego |
Period | 2/28/16 → 3/1/16 |
Funding
This work was supported in part by the National Institutes of Health grant number R01-EB-017226, collaboration with Siemens Healthcare XP, and the Thai Royal Government Scholarship.
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