Advancements in the Management of Spine Disorders

Haldeman, Scott; Kopansky-Giles, Deborah; Hurwitz, Eric L.; Hoy, Damian; Erwin, W. Mark; Dagenais, Simon; Kawchuk, Greg; Strömqvist, Björn; Walsh, Nicolas E.

doi:10.1016/j.berh.2012.03.006

Cited by 73 publications

(58 citation statements)

References 70 publications

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“…Specifically, the stencil for MIND-elastic was a six neighborhood with Δ S = 3 voxels, σ p = 0.5, and α = 0.1 similar to the values used in [24] (see Appendix II.A.3.d). The three-level image pyramids for MIND-elastic and the Demons-based methods were constructed with Gaussian kernel widths of [4, 2, 1] voxels and downsampling factors of [8, 4, 2] voxels, while those for the FFD-based methods were constructed using only Gaussian smoothing without downsampling.…”

Section: Experimental Methodsmentioning

confidence: 99%

“…Spinal disorders are a major cause of disability [1] and cover a broad spectrum of pathologies, such as spinal injury (25% of trauma patients [2]), spine metastases (in 10% of cancer patients [3]), and scoliosis (presenting in up to 32% of adults and 68% of the elderly [4]). Such spinal diseases are treatable by surgery; however, the complexity of spinal structure and function can challenge safe and accurate intervention.…”

Section: Introductionmentioning

confidence: 99%

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MIND Demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery

Reaungamornrat

Silva

Uneri

et al. 2016

IEEE Trans. Med. Imaging

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Intraoperative localization of target anatomy and critical structures defined in preoperative MR/CT images can be achieved through the use of multimodality deformable registration. 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. The method, called MIND Demons, finds a deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the integrated velocity fields, a modality-insensitive similarity function suitable to multimodality images, and smoothness on the diffeomorphisms themselves. Direct optimization without relying on the exponential map and stationary velocity field approximation 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, phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, normalized MI (NMI) Demons, and MIND with a diffusion-based registration method (MIND-elastic). The method yielded sub-voxel invertibility (0.008 mm) and nonzero-positive Jacobian determinants. It also showed improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.7 mm compared to 11.3, 3.1, 5.6, and 2.4 mm for MI FFD, LMI FFD, NMI Demons, and MIND-elastic methods, respectively. Validation in clinical studies demonstrated realistic deformations with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine.

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Section: Experimental Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MIND Demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery

Reaungamornrat

Silva

Uneri

et al. 2016

IEEE Trans. Med. Imaging

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“…Hereditary and environmental factors such as age, weight, height, gender, occupation, smoking, exposure to vibration, and genetic factors have all been implicated in its causation [1,2]. Occupational conditions are known to induce degenerative joint changes as a result of increased load to the spine, knees and hips, due to monotonous and repetitive body position that leads to injury of the nervous and circulatory system, leading to damage and pain [3][4][5].…”

Section: Introductionmentioning

confidence: 98%

Association between bone scintigraphy features of spinal degeneration and anthropometric and demographic variables

Chatziioannou

Kallergi

Karampina

et al. 2015

BMR

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“…1 They cover a broad spectrum of pathologies, such as spinal injury in 25% of trauma patients, 2 spine metastases identified in 10% of patients with cancer, 3 and scoliosis presenting in 2–32% of adults and 68% of elderly patients. 4 Such spinal diseases are treatable by surgery; however, the complexity of spinal structure and function can challenge safe and accurate intervention.…”

Section: Introductionmentioning

confidence: 99%

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

Reaungamornrat

Silva

Uneri

et al. 2016

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

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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.

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Advancements in the Management of Spine Disorders

Cited by 73 publications

References 70 publications

MIND Demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery

MIND Demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery

Association between bone scintigraphy features of spinal degeneration and anthropometric and demographic variables

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

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