Non-invasive, fluoroscopy-based, image-guided surgery reduces radiation exposure for vertebral compression fractures: A preliminary survey

Yang, Chih-Dong; Chen, Yuwei; Tseng, Ching-Shiow; Ho, Hsin-Ju; Wu, Chi-Chun; Wang, Kuo-Wei

doi:10.1016/j.fjs.2011.12.003

Cited by 9 publications

(6 citation statements)

References 12 publications

(8 reference statements)

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“…This additional complexity is mitigated by advances in medical imaging technologies such as computed tomography (CT), magnetic resonance (MRI), and ultrasound (US) imaging, where preoperative and intraoperative medical images are acquired before and during surgery to assist surgeons in planning the surgery and in guiding surgical tool manipulation. Various clinical investigations [1][2][3] have demonstrated that the use of medical image-guidance is able to reduce risk of errors and improve the success rate of operations.…”

Section: Introductionmentioning

confidence: 99%

Augmented Reality Guidance with Multimodality Imaging Data and Depth-Perceived Interaction for Robot-Assisted Surgery

2017

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Image-guided surgical procedures are challenged by mono image modality, twodimensional anatomical guidance and non-intuitive human-machine interaction. The introduction of Tablet-based augmented reality (AR) into surgical robots may assist surgeons with overcoming these problems. In this paper, we proposed and developed a robot-assisted surgical system with interactive surgical guidance using tablet-based AR with a Kinect sensor for three-dimensional (3D) localization of patient anatomical structures and intraoperative 3D surgical tool navigation. Depth data acquired from the Kinect sensor was visualized in cone-shaped layers for 3D AR-assisted navigation. Virtual visual cues generated by the tablet were overlaid on the images of the surgical field for spatial reference. We evaluated the proposed system and the experimental results showed that the tablet-based visual guidance system could assist surgeons in locating internal organs, with errors between 1.74 and 2.96 mm. We also demonstrated that the system was able to provide mobile augmented guidance and interaction for surgical tool navigation.

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Section: Introductionmentioning

confidence: 99%

Augmented Reality Guidance with Multimodality Imaging Data and Depth-Perceived Interaction for Robot-Assisted Surgery

2017

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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%

“…Comparison are shown to MIND-elastic, since the MIND Demons and MIND-elastic methods demonstrated the best registration performance among the methods investigated in the phantom studies (see Sections III.B.2 and IV.A). The studies used a four-level morphological pyramid with Gaussian kernel widths of [8, 4, 2, 1] voxels and downsampling factors of [16, 8, 4, 2] voxels.…”

Section: Experimental Methodsmentioning

confidence: 99%

“…Such spinal diseases are treatable by surgery; however, the complexity of spinal structure and function can challenge safe and accurate intervention. Especially for minimally invasive surgical approaches, image guidance improves the localization of target anatomy (e.g., vertebral levels and tumors) and critical structures (e.g., nervous and vascular systems) and has been shown to improve surgical accuracy and outcomes in pedicle screw placement [5], [6], correction of spinal deformities [5], [6], trauma surgery [7], percutaneous vertebroplasty [8], and resection of tumors [9]. …”

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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“…4 Such spinal diseases are treatable by surgery; however, the complexity of spinal structure and function can challenge safe and accurate intervention. Image-guided spine surgery (IGSS) has been shown to improve surgical accuracy and outcomes in pedicle screw placement, 5,6 correction of spinal deformities, 5,6 trauma surgery, 7 percutaneous vertebroplasty, 8 and resection of tumors. 9 In IGSS, preoperative MR often provides a basis for definition of target anatomy (e.g., vertebral levels and tumors) and critical structures (e.g., nervous and vascular systems), and localization in intraoperative CT requires multimodality registration capable of resolving significant deformation (e.g., supine MR to prone, kyphosed intraoperative CT).…”

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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Non-invasive, fluoroscopy-based, image-guided surgery reduces radiation exposure for vertebral compression fractures: A preliminary survey

Cited by 9 publications

References 12 publications

Augmented Reality Guidance with Multimodality Imaging Data and Depth-Perceived Interaction for Robot-Assisted Surgery

Augmented Reality Guidance with Multimodality Imaging Data and Depth-Perceived Interaction for Robot-Assisted Surgery

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

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

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