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

doi:10.1117/12.2208621

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

Neurological Surgery

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 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 language	English (US)
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	https://doi.org/10.1117/12.2208621
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
Volume	9786
ISSN (Print)	1605-7422

Other

Other	Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling
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

Access to Document

10.1117/12.2208621

Cite this

Reaungamornrat, S., De Silva, T., Uneri, A., Wolinsky, J. P., Khanna, A. J., Kleinszig, G., Vogt, S., Prince, J. L., & Siewerdsen, J. H. (2016). MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery. In R. J. Webster, & Z. R. Yaniv (Eds.), Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling Article 97860H (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9786). SPIE. https://doi.org/10.1117/12.2208621

@inproceedings{367a94b489654d078f494c050cc54c67,

title = "MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery",

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.",

keywords = "CT, Demons algorithm, MIND, MRI, deformable image registration, image-guided surgery, multimodality image registration, symmetric diffeomorphism",

author = "S. Reaungamornrat and \{De Silva\}, T. and A. Uneri and Wolinsky, \{J. P.\} and Khanna, \{A. J.\} and G. Kleinszig and S. Vogt and Prince, \{J. L.\} and Siewerdsen, \{J. H.\}",

note = "Funding Information: 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. Publisher Copyright: {\textcopyright} 2016 SPIE.; Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling ; Conference date: 28-02-2016 Through 01-03-2016",

year = "2016",

doi = "10.1117/12.2208621",

language = "English (US)",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

publisher = "SPIE",

editor = "Webster, \{Robert J.\} and Yaniv, \{Ziv R.\}",

booktitle = "Medical Imaging 2016",

}

Reaungamornrat, S, De Silva, T, Uneri, A, Wolinsky, JP, Khanna, AJ, Kleinszig, G, Vogt, S, Prince, JL & Siewerdsen, JH 2016, MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery. in RJ Webster & ZR Yaniv (eds), Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling., 97860H, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 9786, SPIE, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, San Diego, United States, 2/28/16. https://doi.org/10.1117/12.2208621

MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery. / Reaungamornrat, S.; De Silva, T.; Uneri, A. et al.
Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling. ed. / Robert J. Webster; Ziv R. Yaniv. SPIE, 2016. 97860H (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9786).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery

AU - Reaungamornrat, S.

AU - De Silva, T.

AU - Uneri, A.

AU - Wolinsky, J. P.

AU - Khanna, A. J.

AU - Kleinszig, G.

AU - Vogt, S.

AU - Prince, J. L.

AU - Siewerdsen, J. H.

N1 - Funding Information: 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. Publisher Copyright: © 2016 SPIE.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - CT

KW - Demons algorithm

KW - MIND

KW - MRI

KW - deformable image registration

KW - image-guided surgery

KW - multimodality image registration

KW - symmetric diffeomorphism

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DO - 10.1117/12.2208621

M3 - Conference contribution

C2 - 27330239

AN - SCOPUS:84982187972

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2016

A2 - Webster, Robert J.

A2 - Yaniv, Ziv R.

PB - SPIE

T2 - Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling

Y2 - 28 February 2016 through 1 March 2016

ER -

Reaungamornrat S, De Silva T, Uneri A, Wolinsky JP, Khanna AJ, Kleinszig G et al. MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery. In Webster RJ, Yaniv ZR, editors, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling. SPIE. 2016. 97860H. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). doi: 10.1117/12.2208621

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

Abstract

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