Dr. Yoshito Otake Profile

Dr. Yoshito Otake

Associate Research Scientist at Johns Hopkins Univ

SPIE Involvement:

Author

Publications (41)

Proceedings Article | 3 April 2024 Poster + Paper

Performance improvement for medical image classification model by using gradient-based analytical feature selection

Ryo Toda, Hayato Itoh, Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

Proceedings Volume 12927, 129272C (2024) https://doi.org/10.1117/12.3006620

KEYWORDS: Visualization, Visual process modeling, Feature selection, Image classification, COVID 19, Data modeling, Medical imaging, Image analysis

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Proceedings Article | 7 April 2023 Poster + Paper

Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-mixer

Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

Proceedings Volume 12465, 1246534 (2023) https://doi.org/10.1117/12.2654706

KEYWORDS: 3D modeling, 3D image processing, COVID 19, Image classification, Chest, Computed tomography, Lung

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Proceedings Article | 7 April 2023 Presentation + Paper

Improved method for COVID-19 classification of complex-architecture CNN from chest CT volumes using orthogonal ensemble networks

Ryo Toda, Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

Proceedings Volume 12465, 124650D (2023) https://doi.org/10.1117/12.2653792

KEYWORDS: COVID 19, Computed tomography, Machine learning, Education and training, Chest, Feature extraction, Lung, Computer aided detection

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Proceedings Article | 4 April 2022 Presentation + Paper

Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumes

Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori

Proceedings Volume 12033, 1203309 (2022) https://doi.org/10.1117/12.2613317

KEYWORDS: Feature extraction, Chest, Computed tomography, Lung, Convolution, 3D image processing, Image processing, Image classification, CAD systems

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Proceedings Article | 20 April 2021 Paper

Analysis of multiplanar integration based on uncertainty estimation in automatic segmentation of abdominal organs in 3D CT image using 2D Bayesian U-Net

Yuto Masaki, Yoshito Otake, Mazen Soufi, Masatoshi Hori, Hiromitsu Onishi, Noriyuki Tomiyama, Yoshinobu Sato

Proceedings Volume 11792, 1179208 (2021) https://doi.org/10.1117/12.2590794

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Extraction of lung and lesion regions from COVID-19 CT volumes using 3D fully convolutional networks

Yuichiro Hayashi, Masahiro Oda, Chen Shen, Masahiro Hashimoto, Yoshito Otake, Toshiaki Akashi, Kensaku Mori

Proceedings Volume 11597, 115972A (2021) https://doi.org/10.1117/12.2581818

KEYWORDS: Lung, 3D modeling, Computed tomography, CAD systems, Medical imaging, Solid modeling, Image segmentation, Data modeling, Computer aided diagnosis and therapy

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Lung infection and normal region segmentation from CT volumes of COVID-19 cases

Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Kensaku Mori

Proceedings Volume 11597, 115972X (2021) https://doi.org/10.1117/12.2582066

KEYWORDS: Lung, Image segmentation, Computing systems, Quantitative analysis, Diagnostics, Chest

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Unsupervised segmentation of COVID-19 infected lung clinical CT volumes using image inpainting and representation learning

Tong Zheng, Masahiro Oda, Chenglong Wang, Takayasu Moriya, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Kensaku Mori

Proceedings Volume 11596, 115963F (2021) https://doi.org/10.1117/12.2580641

KEYWORDS: Image segmentation, Computed tomography, Chest, Arteries, Spherical lenses, Lung, Tissues, Opacity, Glasses

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Proceedings Article | 27 March 2019 Paper

Automated segmentation of hip and thigh muscles in metal artifact contaminated CT using CNN

Mitsuki Sakamoto, Yuta Hiasa, Yoshito Otake, Masaki Takao, Yuki Suzuki, Nobuhiko Sugano, Yoshinobu Sato

Proceedings Volume 11050, 110500S (2019) https://doi.org/10.1117/12.2521440

KEYWORDS: Image segmentation, Metals, Computed tomography, Surgery, Computer simulations, Image processing algorithms and systems, X-ray computed tomography, Image analysis, Convolutional neural networks

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Proceedings Article | 9 March 2017 Presentation + Paper

False dyssynchrony: problem with image-based cardiac functional analysis using x-ray computed tomography

Masafumi Kidoh, Zeyang Shen, Yuki Suzuki, Luisa Ciuffo, Hiroshi Ashikaga, George S. Fung, Yoshito Otake, Stefan Zimmerman, Joao A. Lima, Takahiro Higuchi, Okkyun Lee, Yoshinobu Sato, Lewis Becker, Elliot Fishman, Katsuyuki Taguchi

Proceedings Volume 10132, 101321U (2017) https://doi.org/10.1117/12.2250257

KEYWORDS: X-ray computed tomography, Functional analysis, Heart, Computed tomography, Motion estimation, CT reconstruction, Magnetic resonance imaging, Temporal resolution, Reconstruction algorithms

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Proceedings Article | 9 March 2017 Paper

Projection-based motion estimation for cardiac functional analysis with high temporal resolution: a proof-of-concept study with digital phantom experiment

Yuki Suzuki, George S. Fung, Zeyang Shen, Yoshito Otake, Okkyun Lee, Luisa Ciuffo, Hiroshi Ashikaga, Yoshinobu Sato, Katsuyuki Taguchi

Proceedings Volume 10132, 1013230 (2017) https://doi.org/10.1117/12.2254723

KEYWORDS: X-ray computed tomography, Heart, Medical imaging, Error analysis, Motion estimation, Motion analysis, Functional analysis, Temporal resolution, Image registration, Statistical analysis, Image resolution, 3D image processing, Image quality, Image restoration

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Proceedings Article | 21 March 2016 Paper

Automated segmentation of upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical modeling of organ interrelations

S. Hirayama, Y. Otake, T. Okada, M. Hori, N. Tomiyama, Y. Sato

Proceedings Volume 9784, 97840F (2016) https://doi.org/10.1117/12.2216593

KEYWORDS: Image segmentation, Statistical analysis, Esophagus, Stomach, Data modeling, Machine learning, Computed tomography, Liver, Pancreas, Statistical modeling, Medical imaging

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Proceedings Article | 18 March 2016 Paper

Robust patella motion tracking using intensity-based 2D-3D registration on dynamic bi-plane fluoroscopy: towards quantitative assessment in MPFL reconstruction surgery

Yoshito Otake, Matthieu Esnault, Robert Grupp, Shinichi Kosugi, Yoshinobu Sato

Proceedings Volume 9786, 97860B (2016) https://doi.org/10.1117/12.2214699

KEYWORDS: Image registration, Computed tomography, Fluoroscopy, Motion measurement, In vivo imaging, 3D metrology, 3D image processing, Kinematics, Visualization, Optimization (mathematics)

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Proceedings Article | 18 March 2015 Paper

Rendering-based video-CT registration with physical constraints for image-guided endoscopic sinus surgery

Y. Otake, S. Leonard, A. Reiter, P. Rajan, J. Siewerdsen, G. Gallia, M. Ishii, R. Taylor, G. Hager

Proceedings Volume 9415, 94150A (2015) https://doi.org/10.1117/12.2081732

KEYWORDS: Endoscopes, Image registration, Computed tomography, Endoscopy, Surgery, Optimization (mathematics), Cameras, Image-guided intervention, Stochastic processes, 3D modeling

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Proceedings Article | 18 March 2015 Paper

Comparison of optimization strategy and similarity metric in atlas-to-subject registration using statistical deformation model

Y. Otake, R. Murphy, R. Grupp, Y. Sato, R. Taylor, M. Armand

Proceedings Volume 9415, 94150Q (2015) https://doi.org/10.1117/12.2081754

KEYWORDS: Image registration, Optimization (mathematics), Statistical modeling, Principal component analysis, Error analysis, Evolutionary optimization, Computed tomography, Surgery, Phased array optics, Statistical analysis

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Proceedings Article | 18 March 2015 Paper

Smooth extrapolation of unknown anatomy via statistical shape models

R. Grupp, H. Chiang, Y. Otake, R. Murphy, C. Gordon, M. Armand, R. Taylor

Proceedings Volume 9415, 941524 (2015) https://doi.org/10.1117/12.2081310

KEYWORDS: Skull, Error analysis, Statistical modeling, Medical imaging, Computed tomography, Data modeling, Surgery, Statistical analysis, Bone, Solids

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Proceedings Article | 19 March 2014 Paper

Patient-specific minimum-dose imaging protocols for statistical image reconstruction in C-arm cone-beam CT using correlated noise injection

A. Wang, J. Stayman, Y. Otake, A. Khanna, G. Gallia, J. Siewerdsen

Proceedings Volume 9033, 90331P (2014) https://doi.org/10.1117/12.2043083

KEYWORDS: Image quality, Sensors, Spatial resolution, Interference (communication), Image restoration, Surgery, X-ray computed tomography, Electronics, Head, Performance modeling

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Purpose: A new method for accurately portraying the impact of low-dose imaging techniques in C-arm cone-beam CT (CBCT) is presented and validated, allowing identification of minimum-dose protocols suitable to a given imaging task on a patient-specific basis in scenarios that require repeat intraoperative scans. Method: To accurately simulate lower-dose techniques and account for object-dependent noise levels (x-ray quantum noise and detector electronics noise) and correlations (detector blur), noise of the proper magnitude and correlation was injected into the projections from an initial CBCT acquired at the beginning of a procedure. The resulting noisy projections were then reconstructed to yield low-dose preview (LDP) images that accurately depict the image quality at any level of reduced dose in both filtered backprojection and statistical image reconstruction. Validation studies were conducted on a mobile C-arm, with the noise injection method applied to images of an anthropomorphic head phantom and cadaveric torso across a range of lower-dose techniques. Results: Comparison of preview and real CBCT images across a full range of techniques demonstrated accurate noise magnitude (within ~5%) and correlation (matching noise-power spectrum, NPS). Other image quality characteristics (e.g., spatial resolution, contrast, and artifacts associated with beam hardening and scatter) were also realistically presented at all levels of dose and across reconstruction methods, including statistical reconstruction. Conclusion: Generating low-dose preview images for a broad range of protocols gives a useful method to select minimum-dose techniques that accounts for complex factors of imaging task, patient-specific anatomy, and observer preference. The ability to accurately simulate the influence of low-dose acquisition in statistical reconstruction provides an especially valuable means of identifying low-dose limits in a manner that does not rely on a model for the nonlinear reconstruction process or a model of observer performance.

Proceedings Article | 12 March 2014 Paper

Piecewise-rigid 2D-3D registration for pose estimation of snake-like manipulator using an intraoperative x-ray projection

Y. Otake, R. Murphy, M. Kutzer, R. Taylor, M. Armand

Proceedings Volume 9036, 90360Q (2014) https://doi.org/10.1117/12.2043242

KEYWORDS: Kinematics, Image registration, X-rays, Calibration, Surgery, X-ray imaging, Radiography, Video, Spine, Electrodes

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Background: Snake-like dexterous manipulators may offer significant advantages in minimally-invasive surgery in areas not reachable with conventional tools. Precise control of a wire-driven manipulator is challenging due to factors such as cable deformation, unknown internal (cable friction) and external forces, thus requiring correcting the calibration intraoperatively by determining the actual pose of the manipulator. Method: A method for simultaneously estimating pose and kinematic configuration of a piecewise-rigid object such as a snake-like manipulator from a single x-ray projection is presented. The method parameterizes kinematics using a small number of variables (e.g., 5), and optimizes them simultaneously with the 6 degree-of-freedom pose parameter of the base link using an image similarity between digitally reconstructed radiographs (DRRs) of the manipulator’s attenuation model and the real x-ray projection. Result: Simulation studies assumed various geometric magnifications (1.2–2.6) and out-of-plane angulations (0°–90°) in a scenario of hip osteolysis treatment, which demonstrated the median joint angle error was 0.04° (for 2.0 magnification, ±10° out-of-plane rotation). Average computation time was 57.6 sec with 82,953 function evaluations on a mid-range GPU. The joint angle error remained lower than 0.07° while out-of-plane rotation was 0°–60°. An experiment using video images of a real manipulator demonstrated a similar trend as the simulation study except for slightly larger error around the tip attributed to accumulation of errors induced by deformation around each joint not modeled with a simple pin joint. Conclusions: The proposed approach enables high precision tracking of a piecewise-rigid object (i.e., a series of connected rigid structures) using a single projection image by incorporating prior knowledge about the shape and kinematic behavior of the object (e.g., each rigid structure connected by a pin joint parameterized by a low degree polynomial basis). Potential applications of the proposed approach include pose estimation of vertebrae in spine and a series of electrodes in coronary sinus catheter. Improvement of GPU performance is expected to further augment computational speed.

Proceedings Article | 12 March 2014 Paper

Deformable registration for image-guided spine surgery: preserving rigid body vertebral morphology in free-form transformations

S. Reaungamornrat, A. Wang, A. Uneri, Y. Otake, Z. Zhao, A. Khanna, J. Siewerdsen

Proceedings Volume 9036, 90360R (2014) https://doi.org/10.1117/12.2043474

KEYWORDS: Image registration, Spine, Surgery, Computed tomography, Image-guided intervention, Tissues, Bone, Neck, Optical spheres, Rigid registration

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Purpose: Deformable registration of preoperative and intraoperative images facilitates accurate localization of target and critical anatomy in image-guided spine surgery. However, conventional deformable registration fails to preserve the morphology of rigid bone anatomy and can impart distortions that confound high-precision intervention. We propose a constrained registration method that preserves rigid morphology while allowing deformation of surrounding soft tissues. Method: The registration method aligns preoperative 3D CT to intraoperative cone-beam CT (CBCT) using free-form deformation (FFD) with penalties on rigid body motion imposed according to a simple intensity threshold. The penalties enforced 3 properties of a rigid transformation – namely, constraints on affinity (AC), orthogonality (OC), and properness (PC). The method also incorporated an injectivity constraint (IC) to preserve topology. Physical experiments (involving phantoms, an ovine spine, and a human cadaver) as well as digital simulations were performed to evaluate the sensitivity to registration parameters, preservation of rigid body morphology, and overall registration accuracy of constrained FFD in comparison to conventional unconstrained FFD (denoted uFFD) and Demons registration. Result: FFD with orthogonality and injectivity constraints (denoted FFD+OC+IC) demonstrated improved performance compared to uFFD and Demons. Affinity and properness constraints offered little or no additional improvement. The FFD+OC+IC method preserved rigid body morphology at near-ideal values of zero dilatation (D = 0.05, compared to 0.39 and 0.56 for uFFD and Demons, respectively) and shear (S = 0.08, compared to 0.36 and 0.44 for uFFD and Demons, respectively). Target registration error (TRE) was similarly improved for FFD+OC+IC (0.7 mm), compared to 1.4 and 1.8 mm for uFFD and Demons. Results were validated in human cadaver studies using CT and CBCT images, with FFD+OC+IC providing excellent preservation of rigid morphology and equivalent or improved TRE. Conclusions: A promising method for deformable registration in CBCT-guided spine surgery has been identified incorporating a constrained FFD to preserve bone morphology. The approach overcomes distortions intrinsic to unconstrained FFD and could better facilitate high-precision image-guided spine surgery.

Proceedings Article | 12 March 2014 Paper

Dual-projection 3D-2D registration for surgical guidance: preclinical evaluation of performance and minimum angular separation

A. Uneri, Y. Otake, A. Wang, G. Kleinszig, S. Vogt, G. Gallia, D. Rigamonti, J.-P. Wolinsky, Ziya Gokaslan, A. Khanna, J. Siewerdsen

Proceedings Volume 9036, 90362E (2014) https://doi.org/10.1117/12.2043561

KEYWORDS: Image registration, X-rays, 3D acquisition, 3D image processing, Fluoroscopy, X-ray computed tomography, Sensors, Adaptive optics, Surgery, Algorithm development

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Proceedings Article | 19 March 2013 Paper

Soft-tissue imaging in low-dose, C-arm cone-beam CT using statistical image reconstruction

Adam Wang, Sebastian Schafer, J. Stayman, Yoshi Otake, Marc Sussman, A. Khanna, Gary Gallia, Jeffrey Siewerdsen

Proceedings Volume 8668, 86681F (2013) https://doi.org/10.1117/12.2008421

KEYWORDS: Spatial resolution, Image quality, Head, Tissues, Bone, Sensors, Computed tomography, Image resolution, Surgery, 3D image reconstruction

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Proceedings Article | 19 March 2013 Paper

Overcoming nonlinear partial volume effects in known-component reconstruction of Cochlear implants

J. Stayman, H. Dang, Y. Otake, Wojciech Zbijewski, J. Noble, B. Dawant, R. Labadie, J. Carey, J. Siewerdsen

Proceedings Volume 8668, 86681L (2013) https://doi.org/10.1117/12.2007945

KEYWORDS: Sensors, Electrodes, Data modeling, Image registration, Spatial resolution, Model-based design, Signal attenuation, Visualization, Metals, Image resolution

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Proceedings Article | 15 March 2013 Paper

Intraoperative imaging for patient safety and QA: detection of intracranial hemorrhage using C-arm cone-beam CT

Sebastian Schafer, Adam Wang, Yoshito Otake, J. Stayman, Wojciech Zbijewski, Gerhard Kleinszig, Xuewei Xia, Gary Gallia, Jeffrey Siewerdsen

Proceedings Volume 8671, 86711X (2013) https://doi.org/10.1117/12.2008043

KEYWORDS: Spatial resolution, Safety, Blood, X-ray computed tomography, Surgery, Image restoration, Visibility, 3D image reconstruction, Head, Image quality

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Proceedings Article | 15 March 2013 Paper

Deformable image registration with content mismatch: a demons variant to account for added material and surgical devices in the target image

S. Nithiananthan, A. Uneri, S. Schafer, D. Mirota, Y. Otake, J. Stayman, W. Zbijewski, A. Khanna, D. Reh, G. Gallia, J. Siewerdsen

Proceedings Volume 8671, 86712A (2013) https://doi.org/10.1117/12.2008410

KEYWORDS: Image registration, Image segmentation, Tissues, Distortion, Cements, Image processing, Image-guided intervention, Detection and tracking algorithms, Image processing algorithms and systems, Surgery

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Proceedings Article | 12 March 2013 Paper

Model-based cone-beam CT reconstruction for image-guided minimally invasive treatment of hip osteolysis

Yoshito Otake, J. Stayman, W. Zbijewski, R. Murphy, M. Kutzer, R. Taylor, J. Siewerdsen, M. Armand

Proceedings Volume 8671, 86710Y (2013) https://doi.org/10.1117/12.2008094

KEYWORDS: Image registration, Image quality, Model-based design, X-rays, Surgery, X-ray imaging, X-ray computed tomography, Reconstruction algorithms, Signal attenuation, CT reconstruction

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Purpose: Accurate assessment of the size and location of osteolytic regions is essential in minimally invasive hip revision surgery. Moreover, image-guided robotic intervention for osteolysis treatment requires precise localization of implant components. However, high density metallic implants in proximity to the hip make assessment by either 2D or 3D x-ray imaging difficult. This paper details the initial implementation and evaluation of an advanced model-based conebeam CT (CBCT) reconstruction algorithm to improve guidance and assessment of hip osteolysis treatment. Method: A model-based reconstruction approach called Known Component Reconstruction (KCR) was employed to obtain high-quality reconstruction of regions neighboring metallic implants. KCR incorporates knowledge about the implant shape and material to precisely reconstruct surrounding anatomy while simultaneously estimating implant position. A simulation study involving a phantom generated from a CBCT scan of a cadaveric hip was performed. Registration accuracy in KCR iterations was evaluated as translational and rotational error from the true registration. Improvement in image quality was evaluated using normalized cross correlation (NCC) in two regions of interest (ROIs) about the femoral and acetabular components. Result: The study showed significant improvement in image quality over conventional filtered backprojection (FBP) and penalized-likelihood (PL) reconstruction. The NCC in the two ROIs improved from 0.74 and 0.81 (FBP) to 0.98 and 0.86 (PL) and >0.99 for KCR. The registration error was 0.01 mm in translation (0.02° in rotation) for the acetabular component and 0.01 mm (0.01° rotation) for the femoral component. Conclusions: Application of KCR to imaging hip osteolysis in the presence of the implant offers a promising step toward quantitative assessment in minimally invasive image-guided osteolysis treatment. The method improves image quality (metal artifact reduction), yields a precise registration estimate of the implant, and offers a means for reducing radiation dose in intraoperative CBCT.

Proceedings Article | 8 March 2013 Paper

A gaussian mixture + demons deformable registration method for cone-beam CT-guided robotic transoral base-of-tongue surgery

S. Reaungamornrat, W. Liu, S. Schafer, Y. Otake, S. Nithiananthan, A. Uneri, J. Richmon, J. Sorger, J. Siewerdsen, R. Taylor

Proceedings Volume 8671, 86710J (2013) https://doi.org/10.1117/12.2007937

KEYWORDS: Image registration, Image segmentation, Tongue, Computed tomography, Clouds, Magnetic resonance imaging, Rigid registration, Surgery, Video, Mouth

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Purpose: An increasingly popular minimally invasive approach to resection of oropharyngeal / base-of-tongue cancer is made possible by a transoral technique conducted with the assistance of a surgical robot. However, the highly deformed surgical setup (neck flexed, mouth open, and tongue retracted) compared to the typical patient orientation in preoperative images poses a challenge to guidance and localization of the tumor target and adjacent critical anatomy. Intraoperative cone-beam CT (CBCT) can account for such deformation, but due to the low contrast of soft-tissue in CBCT images, direct localization of the target and critical tissues in CBCT images can be difficult. Such structures may be more readily delineated in preoperative CT or MR images, so a method to deformably register such information to intraoperative CBCT could offer significant value. This paper details the initial implementation of a deformable registration framework to align preoperative images with the deformed intraoperative scene and gives preliminary evaluation of the geometric accuracy of registration in CBCT-guided TORS. Method: The deformable registration aligns preoperative CT or MR to intraoperative CBCT by integrating two established approaches. The volume of interest is first segmented (specifically, the region of the tongue from the tip to the hyoid), and a Gaussian mixture (GM) mode1 of surface point clouds is used for rigid initialization (GMRigid) as well as an initial deformation (GMNonRigid). Next, refinement of the registration is performed using the Demons algorithm applied to distance transformations of the GM-registered and CBCT volumes. The registration accuracy of the framework was quantified in preliminary studies using a cadaver emulating preoperative and intraoperative setups. Geometric accuracy of registration was quantified in terms of target registration error (TRE) and surface distance error. Result: With each step of the registration process, the framework demonstrated improved registration, achieving mean TRE of 3.0 mm following the GM rigid, 1.9 mm following GM nonrigid, and 1.5 mm at the output of the registration process. Analysis of surface distance demonstrated a corresponding improvement of 2.2, 0.4, and 0.3 mm, respectively. The evaluation of registration error revealed the accurate alignment in the region of interest for base-of-tongue robotic surgery owing to point-set selection in the GM steps and refinement in the deep aspect of the tongue in the Demons step. Conclusions: A promising framework has been developed for CBCT-guided TORS in which intraoperative CBCT provides a basis for registration of preoperative images to the highly deformed intraoperative setup. The registration framework is invariant to imaging modality (accommodating preoperative CT or MR) and is robust against CBCT intensity variations and artifact, provided corresponding segmentation of the volume of interest. The approach could facilitate overlay of preoperative planning data directly in stereo-endoscopic video in support of CBCT-guided TORS.

Proceedings Article | 3 March 2012 Paper

Model-based reconstruction of objects with inexactly known components

J. Stayman, Y. Otake, S. Schafer, A. Khanna, J. Prince, J. Siewerdsen

Proceedings Volume 8313, 83131S (2012) https://doi.org/10.1117/12.911202

KEYWORDS: Image registration, Signal attenuation, Spine, Image quality, Metals, Data modeling, Control systems, Visualization, Reconstruction algorithms, Image filtering

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Proceedings Article | 17 February 2012 Paper

A clinical pilot study of a modular video-CT augmentation system for image-guided skull base surgery

Wen Liu, Daniel Mirota, Ali Uneri, Yoshito Otake, Gregory Hager, Douglas Reh, Masaru Ishii, Gary Gallia, Jeffrey Siewerdsen

Proceedings Volume 8316, 831633 (2012) https://doi.org/10.1117/12.911724

KEYWORDS: Calibration, Video, Surgery, Cameras, Endoscopy, Skull, Image registration, Endoscopes, Visualization, Computed tomography

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Proceedings Article | 17 February 2012 Paper

Assessing 3D tunnel position in ACL reconstruction using a novel single image 3D-2D registration

X. Kang, W. P. Yau, Y. Otake, P. Y. S. Cheung, Y. Hu, R. Taylor

Proceedings Volume 8316, 831628 (2012) https://doi.org/10.1117/12.911131

KEYWORDS: 3D modeling, X-rays, 3D image processing, Image registration, 3D image reconstruction, X-ray imaging, Expectation maximization algorithms, X-ray computed tomography, Image restoration, Computed tomography

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Proceedings Article | 17 February 2012 Paper

High-performance C-arm cone-beam CT guidance of thoracic surgery

Sebastian Schafer, Yoshito Otake, Ali Uneri, Daniel Mirota, Sajendra Nithiananthan, J. Stayman, Wojciech Zbijewski, Gerhard Kleinszig, Rainer Graumann, Marc Sussman, Jeffrey Siewerdsen

Proceedings Volume 8316, 83161I (2012) https://doi.org/10.1117/12.911811

KEYWORDS: Lung, Video, Surgery, Image registration, Visibility, Tissues, Computed tomography, Visualization, Tumors, Cameras

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Proceedings Article | 17 February 2012 Paper

Automatic localization of target vertebrae in spine surgery using fast CT-to-fluoroscopy (3D-2D) image registration

Y. Otake, S. Schafer, J. Stayman, W. Zbijewski, G. Kleinszig, R. Graumann, A. J. Khanna, J. Siewerdsen

Proceedings Volume 8316, 83160N (2012) https://doi.org/10.1117/12.911308

KEYWORDS: Surgery, Fluoroscopy, Calibration, Image registration, Spine, X-rays, X-ray computed tomography, X-ray imaging, Computer simulations, Image-guided intervention

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Proceedings Article | 17 February 2012 Paper

Tracker-on-C for cone-beam CT-guided surgery: evaluation of geometric accuracy and clinical applications

S. Reaungamornrat, Y. Otake, A. Uneri, S. Schafer, D. Mirota, S. Nithiananthan, J. W. Stayman, A. J. Khanna, D. Reh, G. Gallia, R. Taylor, J. Siewerdsen

Proceedings Volume 8316, 831609 (2012) https://doi.org/10.1117/12.911454

KEYWORDS: Video, Fluoroscopy, Surgery, X-rays, Optical tracking, Visualization, Spine, Radiography, Image registration, X-ray computed tomography

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Conventional surgical tracking configurations carry a variety of limitations in line-of-sight, geometric accuracy, and mismatch with the surgeon's perspective (for video augmentation). With increasing utilization of mobile C-arms, particularly those allowing cone-beam CT (CBCT), there is opportunity to better integrate surgical trackers at bedside to address such limitations. This paper describes a tracker configuration in which the tracker is mounted directly on the Carm. To maintain registration within a dynamic coordinate system, a reference marker visible across the full C-arm rotation is implemented, and the "Tracker-on-C" configuration is shown to provide improved target registration error (TRE) over a conventional in-room setup - (0.9±0.4) mm vs (1.9±0.7) mm, respectively. The system also can generate digitally reconstructed radiographs (DRRs) from the perspective of a tracked tool ("x-ray flashlight"), the tracker, or the C-arm ("virtual fluoroscopy"), with geometric accuracy in virtual fluoroscopy of (0.4±0.2) mm. Using a video-based tracker, planning data and DRRs can be superimposed on the video scene from a natural perspective over the surgical field, with geometric accuracy (0.8±0.3) pixels for planning data overlay and (0.6±0.4) pixels for DRR overlay across all C-arm angles. The field-of-view of fluoroscopy or CBCT can also be overlaid on real-time video ("Virtual Field Light") to assist C-arm positioning. The fixed transformation between the x-ray image and tracker facilitated quick, accurate intraoperative registration. The workflow and precision associated with a variety of realistic surgical tasks were significantly improved using the Tracker-on-C - for example, nearly a factor of 2 reduction in time required for C-arm positioning, reduction or elimination of dose in "hunting" for a specific fluoroscopic view, and confident placement of the x-ray FOV on the surgical target. The proposed configuration streamlines the integration of C-arm CBCT with realtime tracking and demonstrated utility in a spectrum of image-guided interventions (e.g., spine surgery) benefiting from improved accuracy, enhanced visualization, and reduced radiation exposure.

Proceedings Article | 17 February 2012 Paper

Incorporation of prior knowledge for region of change imaging from sparse scan data in image-guided surgery

J. Lee, J. Stayman, Y. Otake, S. Schafer, W. Zbijewski, A. J. Khanna, J. Prince, J. Siewerdsen

Proceedings Volume 8316, 831603 (2012) https://doi.org/10.1117/12.910850

KEYWORDS: X-rays, Image-guided intervention, X-ray imaging, Image fusion, Surgery, Visualization, Data acquisition, Bone, Image registration, 3D image processing

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Proceedings Article | 14 February 2012 Paper

Deformable registration of the inflated and deflated lung for cone-beam CT-guided thoracic surgery

Ali Uneri, Sajendra Nithiananthan, Sebastian Schafer, Yoshito Otake, J. Webster Stayman, Gerhard Kleinszig, Marc Sussman, Russell Taylor, Jerry Prince, Jeffrey Siewerdsen

Proceedings Volume 8316, 831602 (2012) https://doi.org/10.1117/12.911440

KEYWORDS: Lung, Image registration, Surgery, Image segmentation, Tumors, Detection and tracking algorithms, Visualization, Computed tomography, Lung cancer, Image-guided intervention

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Proceedings Article | 17 March 2011 Paper

Penalized-likelihood reconstruction for sparse data acquisitions with unregistered prior images and compressed sensing penalties

J. Stayman, W. Zbijewski, Y. Otake, A. Uneri, S. Schafer, J. Lee, J. Prince, J. Siewerdsen

Proceedings Volume 7961, 79611L (2011) https://doi.org/10.1117/12.878075

KEYWORDS: Lung, Data acquisition, Image registration, Compressed sensing, Tomography, Image analysis, Data modeling, Surveillance, Signal attenuation, Signal to noise ratio

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Proceedings Article | 2 March 2011 Paper

Correspondenceless 3D-2D registration based on expectation conditional maximization

X. Kang, R. Taylor, M. Armand, Y. Otake, W. P. Yau, P. Y. S. Cheung, Y. Hu

Proceedings Volume 7964, 79642Z (2011) https://doi.org/10.1117/12.878618

KEYWORDS: 3D modeling, Image registration, X-ray imaging, X-rays, 3D image processing, Solid modeling, Expectation maximization algorithms, Physics, Curium, Medical imaging

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Proceedings Article | 2 March 2011 Paper

Incorporating tissue excision in deformable image registration: a modified demons algorithm for cone-beam CT-guided surgery

S. Nithiananthan, D. Mirota, A. Uneri, S. Schafer, Y. Otake, J. W. Stayman, J. H. Siewerdsen

Proceedings Volume 7964, 796404 (2011) https://doi.org/10.1117/12.878258

KEYWORDS: Image registration, Tissues, Algorithm development, Computed tomography, Surgery, Head, Neck, 3D image processing, 3D modeling, Prototyping

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Proceedings Article | 2 March 2011 Paper

Architecture of a high-performance surgical guidance system based on C-arm cone-beam CT: software platform for technical integration and clinical translation

Ali Uneri, Sebastian Schafer, Daniel Mirota, Sajendra Nithiananthan, Yoshito Otake, Sureerat Reaungamornrat, Jongheun Yoo, J. Webster Stayman, Douglas Reh, Gary Gallia, A. Jay Khanna, Gregory Hager, Russell Taylor, Gerhard Kleinszig, Jeffrey Siewerdsen

Proceedings Volume 7964, 796422 (2011) https://doi.org/10.1117/12.878191

KEYWORDS: Surgery, Video, Image registration, Computer architecture, Visualization, Fluoroscopy, Endoscopy, 3D image processing, Imaging systems, Computed tomography

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Intraoperative imaging modalities are becoming more prevalent in recent years, and the need for integration of these modalities with surgical guidance is rising, creating new possibilities as well as challenges. In the context of such emerging technologies and new clinical applications, a software architecture for cone-beam CT (CBCT) guided surgery has been developed with emphasis on binding open-source surgical navigation libraries and integrating intraoperative CBCT with novel, application-specific registration and guidance technologies. The architecture design is focused on accelerating translation of task-specific technical development in a wide range of applications, including orthopaedic, head-and-neck, and thoracic surgeries. The surgical guidance system is interfaced with a prototype mobile C-arm for high-quality CBCT and through a modular software architecture, integration of different tools and devices consistent with surgical workflow in each of these applications is realized. Specific modules are developed according to the surgical task, such as: 3D-3D rigid or deformable registration of preoperative images, surgical planning data, and up-to-date CBCT images; 3D-2D registration of planning and image data in real-time fluoroscopy and/or digitally reconstructed radiographs (DRRs); compatibility with infrared, electromagnetic, and video-based trackers used individually or in hybrid arrangements; augmented overlay of image and planning data in endoscopic or in-room video; real-time "virtual fluoroscopy" computed from GPU-accelerated DRRs; and multi-modality image display. The platform aims to minimize offline data processing by exposing quantitative tools that analyze and communicate factors of geometric precision. The system was translated to preclinical phantom and cadaver studies for assessment of fiducial (FRE) and target registration error (TRE) showing sub-mm accuracy in targeting and video overlay within intraoperative CBCT. The work culminates in the development of a CBCT guidance system (reported here for the first time) that leverages the technical developments in Carm CBCT and associated technologies for realizing a high-performance system for translation to clinical studies.

Proceedings Article | 2 March 2011 Paper

Optimization of multi-image pose recovery of fluoroscope tracking (FTRAC) fiducial in an image-guided femoroplasty system

Wen Liu, Mehran Armand, Yoshito Otake, Russell Taylor

Proceedings Volume 7964, 79641D (2011) https://doi.org/10.1117/12.877800

KEYWORDS: Image registration, Image processing, 3D image processing, Error analysis, Image filtering, X-rays, Image segmentation, Bone, Optical tracking, X-ray imaging

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Proceedings Article | 27 February 2010 Paper

Statistical atlas based extrapolation of CT data

Gouthami Chintalapani, Ryan Murphy, Robert Armiger, Jyri Lepisto, Yoshito Otake, Nobuhiko Sugano, Russell Taylor, Mehran Armand

Proceedings Volume 7625, 762539 (2010) https://doi.org/10.1117/12.845570

KEYWORDS: Computed tomography, Image registration, Data modeling, X-rays, Statistical analysis, Phased array optics, X-ray computed tomography, X-ray imaging, Statistical modeling, Error analysis

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Proceedings Article | 27 February 2010 Paper

An image-guided femoroplasty system: development and initial cadaver studies

Yoshito Otake, Mehran Armand, Ofri Sadowsky, Robert Armiger, Michael Kutzer, Simon Mears, Peter Kazanzides, Russell Taylor

Proceedings Volume 7625, 76250P (2010) https://doi.org/10.1117/12.845458

KEYWORDS: Calibration, X-rays, X-ray imaging, Image registration, Navigation systems, 3D image processing, Surgery, X-ray computed tomography, Bone, Sensors

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Showing 5 of 41 publications

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