2025
Jiang, Xiao; Gang, Grace; Stayman, J. Webster
Joint Estimation of Anatomy and Implants using a Mixed Prior Model Conference Forthcoming
SPIE Medical Imaging, Forthcoming.
BibTeX | Tags: CBCT, Machine Learning/Deep Learning, Metal Artifacts, Regularization Design
@conference{Jiang2025,
title = {Joint Estimation of Anatomy and Implants using a Mixed Prior Model},
author = {Xiao Jiang and Grace Gang and J. Webster Stayman},
year = {2025},
date = {2025-02-20},
booktitle = {SPIE Medical Imaging},
keywords = {CBCT, Machine Learning/Deep Learning, Metal Artifacts, Regularization Design},
pubstate = {forthcoming},
tppubtype = {conference}
}
2023
Reynolds, Tess; Ma, Yiqun; Wang, Tianyu; Mei, Kai; Noël, Peter; Gang, Grace; Stayman, J. Webster
Revealing pelvic structures in the presence of metal hip prostheses via non-circular CBCT orbits Conference
Proc SPIE Medical Imaging, vol. 12466, SPIE, 2023.
Links | BibTeX | Tags: CBCT, Customized Acquisition, Metal Artifacts
@conference{Reynolds2023b,
title = {Revealing pelvic structures in the presence of metal hip prostheses via non-circular CBCT orbits},
author = {Tess Reynolds and Yiqun Ma and Tianyu Wang and Kai Mei and Peter Noël and Grace Gang and J. Webster Stayman },
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660Y/Revealing-pelvic-structures-in-the-presence-of-metal-hip-prostheses/10.1117/12.2652980.full
},
doi = {10.1117/12.2652980},
year = {2023},
date = {2023-04-03},
booktitle = {Proc SPIE Medical Imaging},
volume = {12466},
pages = {228-233},
publisher = {SPIE},
keywords = {CBCT, Customized Acquisition, Metal Artifacts},
pubstate = {published},
tppubtype = {conference}
}
2022
Gang, Grace; Stayman, J. Webster
Universal orbit design for metal artifact elimination Journal Article
In: Physics in Medicine and Biology, vol. 67, iss. 11, 2022.
Links | BibTeX | Tags: Analysis, Customized Acquisition, Metal Artifacts
@article{Gang2022,
title = {Universal orbit design for metal artifact elimination},
author = {Grace Gang and J. Webster Stayman },
url = {https://pubmed.ncbi.nlm.nih.gov/35472761/, https://iopscience.iop.org/article/10.1088/1361-6560/ac6aa0/meta},
doi = {10.1088/1361-6560/ac6aa0 },
year = {2022},
date = {2022-05-23},
journal = {Physics in Medicine and Biology},
volume = {67},
issue = {11},
keywords = {Analysis, Customized Acquisition, Metal Artifacts},
pubstate = {published},
tppubtype = {article}
}
Ma, Yiqun; Gang, Grace; Ehtiati, Tina; Reynolds, Tess; Russ, Tom; Wang, Wenying; Weiss, Clifford; Theodore, Nick; Hong, Kelvin; Siewerdsen, Jeffrey H.; Stayman, J. Webster
Non-circular CBCT orbit design and realization on a clinical robotic C-arm for metal artifact reduction Proceedings Article
In: SPIE Medical Imaging, 2022.
Links | BibTeX | Tags: CBCT, Customized Acquisition, Metal Artifacts, Task-Driven Imaging
@inproceedings{Ma2022,
title = {Non-circular CBCT orbit design and realization on a clinical robotic C-arm for metal artifact reduction},
author = {Yiqun Ma and Grace Gang and Tina Ehtiati and Tess Reynolds and Tom Russ and Wenying Wang and Clifford Weiss and Nick Theodore and Kelvin Hong and Jeffrey H. Siewerdsen and J. Webster Stayman },
url = {https://pubmed.ncbi.nlm.nih.gov/35599746/, https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12034/120340A/Non-circular-CBCT-orbit-design-and-realization-on-a-clinical/10.1117/12.2612448.full},
doi = { 10.1117/12.2612448 },
year = {2022},
date = {2022-04-04},
booktitle = {SPIE Medical Imaging},
volume = {12034},
keywords = {CBCT, Customized Acquisition, Metal Artifacts, Task-Driven Imaging},
pubstate = {published},
tppubtype = {inproceedings}
}
2021
Liu, Stephen; Siewerdsen, Jeffrey H.; Stayman, J. Webster; Zbijewski, Wojciech
Quantitative dual-energy imaging in the presence of metal implants using locally constrained model-based decomposition Proceedings Article
In: SPIE Medical Imaging, pp. 115951C, International Society for Optics and Photonics, 2021.
Links | BibTeX | Tags: MBIR, Metal Artifacts, Spectral X-ray/CT
@inproceedings{Liu2021,
title = {Quantitative dual-energy imaging in the presence of metal implants using locally constrained model-based decomposition},
author = {Stephen Liu and Jeffrey H. Siewerdsen and J. Webster Stayman and Wojciech Zbijewski},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11595/115951C/Quantitative-dual-energy-imaging-in-the-presence-of-metal-implants/10.1117/12.2582277.full},
doi = {10.1117/12.2582277},
year = {2021},
date = {2021-02-15},
booktitle = {SPIE Medical Imaging},
volume = {11595},
pages = {115951C},
publisher = {International Society for Optics and Photonics},
keywords = {MBIR, Metal Artifacts, Spectral X-ray/CT},
pubstate = {published},
tppubtype = {inproceedings}
}
2020
Liu, Stephen; Cao, Qian; Tivnan, Matt; Tilley, Steven; Siewerdsen, Jeffrey H.; Stayman, J. Webster; Zbijewski, Wojciech
Model-based dual-energy tomographic image reconstruction of objects containing known metal components Journal Article
In: Physics in Medicine and Biology, vol. 65, no. 24, pp. 245046, 2020.
Links | BibTeX | Tags: Artifact Correction, Known Components, MBIR, Metal Artifacts, Spectral X-ray/CT
@article{Liu2020bb,
title = {Model-based dual-energy tomographic image reconstruction of objects containing known metal components},
author = {Stephen Liu and Qian Cao and Matt Tivnan and Steven Tilley and Jeffrey H. Siewerdsen and J. Webster Stayman and Wojciech Zbijewski},
url = {https://pubmed.ncbi.nlm.nih.gov/33113519/},
doi = {10.1088/1361-6560/abc5a9},
year = {2020},
date = {2020-12-15},
journal = {Physics in Medicine and Biology},
volume = {65},
number = {24},
pages = {245046},
keywords = {Artifact Correction, Known Components, MBIR, Metal Artifacts, Spectral X-ray/CT},
pubstate = {published},
tppubtype = {article}
}
Gang, Grace; Russ, Tom; Ma, Yiqun; Toennes, Christian; Siewerdsen, Jeffrey H.; Schad, Lothar R.; Stayman, J. Webster
Metal-Tolerant Noncircular Orbit Design and Implementation on Robotic C-Arm Systems Proceedings Article
In: International Conference on Image Formation in X-Ray Computed Tomography, 2020.
Links | BibTeX | Tags: Analysis, CBCT, Customized Acquisition, Image Guided Surgery, MBIR, Metal Artifacts, Task-Driven Imaging
@inproceedings{Gang2020b,
title = {Metal-Tolerant Noncircular Orbit Design and Implementation on Robotic C-Arm Systems},
author = {Grace Gang and Tom Russ and Yiqun Ma and Christian Toennes and Jeffrey H. Siewerdsen and Lothar R. Schad and J. Webster Stayman},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7643882/},
year = {2020},
date = {2020-08-01},
booktitle = {International Conference on Image Formation in X-Ray Computed Tomography},
keywords = {Analysis, CBCT, Customized Acquisition, Image Guided Surgery, MBIR, Metal Artifacts, Task-Driven Imaging},
pubstate = {published},
tppubtype = {inproceedings}
}
Gang, Grace; Siewerdsen, Jeffrey H.; Stayman, J. Webster
Non-circular CT orbit design for elimination of metal artifacts Proceedings Article
In: SPIE Medical Imaging, pp. 1131227, International Society for Optics and Photonics, 2020.
Links | BibTeX | Tags: Analysis, Customized Acquisition, Metal Artifacts, Task-Driven Imaging
@inproceedings{Gang2020,
title = {Non-circular CT orbit design for elimination of metal artifacts},
author = {Grace Gang and Jeffrey H. Siewerdsen and J. Webster Stayman},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654842/},
doi = {10.1117/12.2550203},
year = {2020},
date = {2020-03-16},
booktitle = {SPIE Medical Imaging},
volume = {11312},
pages = {1131227},
publisher = {International Society for Optics and Photonics},
keywords = {Analysis, Customized Acquisition, Metal Artifacts, Task-Driven Imaging},
pubstate = {published},
tppubtype = {inproceedings}
}
2019
Zhang, Xiaoxuan; Uneri, Ali; Stayman, J. Webster; Zygourakis, C. C.; Lo, S. L.; Theodore, Nick; Siewerdsen, Jeffrey H.
Known-component 3D image reconstruction for improved intraoperative imaging in spine surgery: A clinical pilot study Journal Article
In: Medical Physics, vol. 46, no. 8, pp. 3483-95, 2019.
Abstract | Links | BibTeX | Tags: CBCT, Image Guided Surgery, Known Components, MBIR, Metal Artifacts, Spine
@article{Zhang2019b,
title = {Known-component 3D image reconstruction for improved intraoperative imaging in spine surgery: A clinical pilot study},
author = {Xiaoxuan Zhang and Ali Uneri and J. Webster Stayman and C. C. Zygourakis and S. L. Lo and Nick Theodore and Jeffrey H. Siewerdsen},
url = {https://pubmed.ncbi.nlm.nih.gov/31180586/},
doi = {10.1002/mp.13652},
year = {2019},
date = {2019-08-01},
journal = {Medical Physics},
volume = {46},
number = {8},
pages = {3483-95},
abstract = {Purpose: Intraoperative imaging plays an increased role in support of surgical guidance and quality assurance for interventional approaches. However, image quality sufficient to detect complications and provide quantitative assessment of the surgical product is often confounded by image noise and artifacts. In this work, we translated a three-dimensional model-based image reconstruction (referred to as "Known-Component Reconstruction," KC-Recon) for the first time to clinical studies with the aim of resolving both limitations.
Methods: KC-Recon builds upon a penalized weighted least-squares (PWLS) method by incorporating models of surgical instrumentation ("known components") within a joint image registration-reconstruction process to improve image quality. Under IRB approval, a clinical pilot study was conducted with 17 spine surgery patients imaged under informed consent using the O-arm cone-beam CT system (Medtronic, Littleton MA) before and after spinal instrumentation. Volumetric images were generated for each patient using KC-Recon in comparison to conventional filtered backprojection (FBP). Imaging performance prior to instrumentation ("preinstrumentation") was evaluated in terms of soft-tissue contrast-to-noise ratio (CNR) and spatial resolution. The quality of images obtained after the instrumentation ("postinstrumentation") was assessed by quantifying the magnitude of metal artifacts (blooming and streaks) arising from pedicle screws. The potential low-dose advantages of the algorithm were tested by simulating low-dose data (down to one-tenth of the dose of standard protocols) from images acquired at normal dose.
Results: Preinstrumentation images (at normal clinical dose and matched resolution) exhibited an average 24.0% increase in soft-tissue CNR with KC-Recon compared to FBP (N = 16, P = 0.02), improving visualization of paraspinal muscles, major vessels, and other soft-tissues about the spine and abdomen. For a total of 72 screws in postinstrumentation images, KC-Recon yielded a significant reduction in metal artifacts: 66.3% reduction in overestimation of screw shaft width due to blooming (P < 0.0001) and reduction in streaks at the screw tip (65.8% increase in attenuation accuracy, P < 0.0001), enabling clearer depiction of the screw within the pedicle and vertebral body for an assessment of breach. Depending on the imaging task, dose reduction up to an order of magnitude appeared feasible while maintaining soft-tissue visibility and metal artifact reduction.
Conclusions: KC-Recon offers a promising means to improve visualization in the presence of surgical instrumentation and reduce patient dose in image-guided procedures. The improved soft-tissue visibility could facilitate the use of cone-beam CT to soft-tissue surgeries, and the ability to precisely quantify and visualize instrument placement could provide a valuable check against complications in the operating room (cf., postoperative CT).
Keywords: cone-beam CT; image-guided procedures; intraoperative imaging; model-based image reconstruction; patient safety.},
keywords = {CBCT, Image Guided Surgery, Known Components, MBIR, Metal Artifacts, Spine},
pubstate = {published},
tppubtype = {article}
}
Methods: KC-Recon builds upon a penalized weighted least-squares (PWLS) method by incorporating models of surgical instrumentation ("known components") within a joint image registration-reconstruction process to improve image quality. Under IRB approval, a clinical pilot study was conducted with 17 spine surgery patients imaged under informed consent using the O-arm cone-beam CT system (Medtronic, Littleton MA) before and after spinal instrumentation. Volumetric images were generated for each patient using KC-Recon in comparison to conventional filtered backprojection (FBP). Imaging performance prior to instrumentation ("preinstrumentation") was evaluated in terms of soft-tissue contrast-to-noise ratio (CNR) and spatial resolution. The quality of images obtained after the instrumentation ("postinstrumentation") was assessed by quantifying the magnitude of metal artifacts (blooming and streaks) arising from pedicle screws. The potential low-dose advantages of the algorithm were tested by simulating low-dose data (down to one-tenth of the dose of standard protocols) from images acquired at normal dose.
Results: Preinstrumentation images (at normal clinical dose and matched resolution) exhibited an average 24.0% increase in soft-tissue CNR with KC-Recon compared to FBP (N = 16, P = 0.02), improving visualization of paraspinal muscles, major vessels, and other soft-tissues about the spine and abdomen. For a total of 72 screws in postinstrumentation images, KC-Recon yielded a significant reduction in metal artifacts: 66.3% reduction in overestimation of screw shaft width due to blooming (P < 0.0001) and reduction in streaks at the screw tip (65.8% increase in attenuation accuracy, P < 0.0001), enabling clearer depiction of the screw within the pedicle and vertebral body for an assessment of breach. Depending on the imaging task, dose reduction up to an order of magnitude appeared feasible while maintaining soft-tissue visibility and metal artifact reduction.
Conclusions: KC-Recon offers a promising means to improve visualization in the presence of surgical instrumentation and reduce patient dose in image-guided procedures. The improved soft-tissue visibility could facilitate the use of cone-beam CT to soft-tissue surgeries, and the ability to precisely quantify and visualize instrument placement could provide a valuable check against complications in the operating room (cf., postoperative CT).
Keywords: cone-beam CT; image-guided procedures; intraoperative imaging; model-based image reconstruction; patient safety.
Uneri, Ali; Zhang, Xiaoxuan; Yi, T.; Stayman, J. Webster; Helm, Patrick; Osgood, Greg M.; Theodore, Nick; Siewerdsen, Jeffrey H.
Known-component metal artifact reduction (KC-MAR) for cone-beam CT Journal Article
In: Physics in Medicine and Biology, vol. 64, no. 16, pp. 165021 , 2019.
Abstract | Links | BibTeX | Tags: Known Components, Metal Artifacts, Prior Images
@article{Uneri2019b,
title = {Known-component metal artifact reduction (KC-MAR) for cone-beam CT},
author = {Ali Uneri and Xiaoxuan Zhang and T. Yi and J. Webster Stayman and Patrick Helm and Greg M. Osgood and Nick Theodore and Jeffrey H. Siewerdsen},
url = {https://pubmed.ncbi.nlm.nih.gov/31287092/},
doi = {10.1088/1361-6560/ab3036},
year = {2019},
date = {2019-08-01},
journal = {Physics in Medicine and Biology},
volume = {64},
number = {16},
pages = {165021 },
abstract = {Intraoperative cone-beam CT (CBCT) is increasingly used for surgical navigation and validation of device placement. In spinal deformity correction, CBCT provides visualization of pedicle screws and fixation rods in relation to adjacent anatomy. This work reports and evaluates a method that uses prior information regarding such surgical instrumentation for improved metal artifact reduction (MAR). The known-component MAR (KC-MAR) approach achieves precise localization of instrumentation in projection images using rigid or deformable 3D-2D registration of component models, thereby overcoming residual errors associated with segmentation-based methods. Projection data containing metal components are processed via 2D inpainting of the detector signal, followed by 3D filtered back-projection (FBP). Phantom studies were performed to identify nominal algorithm parameters and quantitatively investigate performance over a range of component material composition and size. A cadaver study emulating screw and rod placement in spinal deformity correction was conducted to evaluate performance under realistic clinical imaging conditions. KC-MAR demonstrated reduction in artifacts (standard deviation in voxel values) across a range of component types and dose levels, reducing the artifact to 5-10 HU. Accurate component delineation was demonstrated for rigid (screw) and deformable (rod) models with sub-mm registration errors, and a single-pixel dilation of the projected components was found to compensate for partial-volume effects. Artifacts associated with spine screws and rods were reduced by 40%-80% in cadaver studies, and the resulting images demonstrated markedly improved visualization of instrumentation (e.g. screw threads) within cortical margins. The KC-MAR algorithm combines knowledge of surgical instrumentation with 3D image reconstruction in a manner that overcomes potential pitfalls of segmentation. The approach is compatible with FBP-thereby maintaining simplicity in a manner that is consistent with surgical workflow-or more sophisticated model-based reconstruction methods that could further improve image quality and/or help reduce radiation dose.},
keywords = {Known Components, Metal Artifacts, Prior Images},
pubstate = {published},
tppubtype = {article}
}
Liu, Stephen; Tilley, Steven; Cao, Qian; Siewerdsen, Jeffrey H.; Stayman, J. Webster; Zbijewski, Wojciech
Known-component model-based material decomposition for dual energy imaging of bone compositions in the presence of metal implant Proceedings Article
In: International Meeting on Fully Three-Dimensional Image Reconstruction, Proc. SPIE , pp. 1107213, 2019.
Links | BibTeX | Tags: Extremities, Known Components, MBIR, Metal Artifacts, Spectral X-ray/CT
@inproceedings{Liu2019,
title = {Known-component model-based material decomposition for dual energy imaging of bone compositions in the presence of metal implant},
author = {Stephen Liu and Steven Tilley and Qian Cao and Jeffrey H. Siewerdsen and J. Webster Stayman and Wojciech Zbijewski},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11072/2534725/Known-component-model-based-material-decomposition-for-dual-energy-imaging/10.1117/12.2534725.short
https://pubmed.ncbi.nlm.nih.gov/31359904/},
doi = {10.1117/12.2534725},
year = {2019},
date = {2019-06-02},
booktitle = {International Meeting on Fully Three-Dimensional Image Reconstruction, Proc. SPIE },
volume = {11072},
pages = {1107213},
keywords = {Extremities, Known Components, MBIR, Metal Artifacts, Spectral X-ray/CT},
pubstate = {published},
tppubtype = {inproceedings}
}
2018
Uneri, Ali; Yi, T.; Zhang, Xiaoxuan; Stayman, J. Webster; Helm, Patrick; Osgood, Greg M.; Theodore, Nick; Siewerdsen, Jeffrey H.
3D-2D known-component registration for metal artifact reduction in cone-beam CT Proceedings Article
In: International Conference on Image Formation in X-Ray Computed Tomography, pp. 151-155, 2018.
Links | BibTeX | Tags: Artifact Correction, Image Registration, Known Components, Metal Artifacts, Spine
@inproceedings{Uneri2018b,
title = {3D-2D known-component registration for metal artifact reduction in cone-beam CT},
author = {Ali Uneri and T. Yi and Xiaoxuan Zhang and J. Webster Stayman and Patrick Helm and Greg M. Osgood and Nick Theodore and Jeffrey H. Siewerdsen },
url = {https://aiai.jhu.edu/papers/CT2018_uneri.pdf},
year = {2018},
date = {2018-05-20},
booktitle = {International Conference on Image Formation in X-Ray Computed Tomography},
pages = {151-155},
keywords = {Artifact Correction, Image Registration, Known Components, Metal Artifacts, Spine},
pubstate = {published},
tppubtype = {inproceedings}
}
Uneri, Ali; Zhang, Xiaoxuan; Stayman, J. Webster; Helm, Patrick; Osgood, Greg M.; Theodore, Nick; Siewerdsen, Jeffrey H.
Advanced Image Registration and Reconstruction using the O-Arm System: Dose Reduction, Image Quality, and Guidance using Known-Component Models Proceedings Article
In: Proc. SPIE Medical Imaging, pp. 1015761G-1-7, 2018.
Links | BibTeX | Tags: Image Guided Surgery, Image Registration, Known Components, Metal Artifacts, Spine, System Assessment
@inproceedings{Uneri2018,
title = {Advanced Image Registration and Reconstruction using the O-Arm System: Dose Reduction, Image Quality, and Guidance using Known-Component Models},
author = {Ali Uneri and Xiaoxuan Zhang and J. Webster Stayman and Patrick Helm and Greg M. Osgood and Nick Theodore and Jeffrey H. Siewerdsen},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10576/2293874/Advanced-image-registration-and-reconstruction-using-the-O-Arm-system/10.1117/12.2293874.full},
doi = {10.1117/12.2293874},
year = {2018},
date = {2018-02-15},
booktitle = {Proc. SPIE Medical Imaging},
volume = {10576},
pages = {1015761G-1-7},
keywords = {Image Guided Surgery, Image Registration, Known Components, Metal Artifacts, Spine, System Assessment},
pubstate = {published},
tppubtype = {inproceedings}
}
2017
Xu, Shiyu; Khanna, A. Jay; Siewerdsen, Jeffrey H.; Stayman, J. Webster
Polyenergetic known-component CT reconstruction with unknown material compositions and unknown x-ray spectra Journal Article
In: Physics in medicine and biology, vol. 62, no. 8, pp. 3352-3374, 2017.
Links | BibTeX | Tags: Artifact Correction, Beam Hardening, Known Components, MBIR, Metal Artifacts
@article{Xu2017,
title = {Polyenergetic known-component CT reconstruction with unknown material compositions and unknown x-ray spectra},
author = {Shiyu Xu and A. Jay Khanna and Jeffrey H. Siewerdsen and J. Webster Stayman },
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5728157/
http://iopscience.iop.org/article/10.1088/1361-6560/aa6285/meta
},
doi = {10.1088/1361-6560/aa6285},
year = {2017},
date = {2017-03-28},
journal = {Physics in medicine and biology},
volume = {62},
number = {8},
pages = {3352-3374},
keywords = {Artifact Correction, Beam Hardening, Known Components, MBIR, Metal Artifacts},
pubstate = {published},
tppubtype = {article}
}
Zhang, Chengzhu; Zbijewski, Wojciech; Zhang, Xiaoxuan; Xu, Shiyu; Stayman, J. Webster
Polyenergetic known-component reconstruction without prior shape models Proceedings Article
In: Flohr, Thomas G.; Lo, Joseph Y.; Schmidt, Taly Gilat (Ed.): SPIE Medical Imaging, pp. 101320O-1–6, 2017.
Links | BibTeX | Tags: Beam Hardening, Known Components, MBIR, Metal Artifacts
@inproceedings{Zhang2017,
title = {Polyenergetic known-component reconstruction without prior shape models},
author = {Chengzhu Zhang and Wojciech Zbijewski and Xiaoxuan Zhang and Shiyu Xu and J. Webster Stayman },
editor = {Thomas G. Flohr and Joseph Y. Lo and Taly Gilat Schmidt},
url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2255542},
doi = {10.1117/12.2255542},
year = {2017},
date = {2017-03-01},
booktitle = {SPIE Medical Imaging},
volume = {10132},
pages = {101320O-1--6},
keywords = {Beam Hardening, Known Components, MBIR, Metal Artifacts},
pubstate = {published},
tppubtype = {inproceedings}
}
Zhang, Xiaoxuan; Tilley, Steven; Xu, Shiyu; Mathews, Aswin; McVeigh, Elliot; Stayman, J. Webster
Deformable Known Component Model-Based Reconstruction for Coronary CT Angiography Proceedings Article
In: Flohr, Thomas G.; Lo, Joseph Y.; Schmidt, Taly Gilat (Ed.): SPIE Medical Imaging, pp. 1013213-1–6, 2017.
Links | BibTeX | Tags: Beam Hardening, Cardiac, Image Registration, Known Components, MBIR, Metal Artifacts
@inproceedings{Zhang2017a,
title = {Deformable Known Component Model-Based Reconstruction for Coronary CT Angiography},
author = {Xiaoxuan Zhang and Steven Tilley and Shiyu Xu and Aswin Mathews and Elliot McVeigh and J. Webster Stayman},
editor = {Thomas G. Flohr and Joseph Y. Lo and Taly Gilat Schmidt},
url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2255303},
doi = {10.1117/12.2255303},
year = {2017},
date = {2017-03-01},
booktitle = {SPIE Medical Imaging},
volume = {10132},
pages = {1013213-1--6},
keywords = {Beam Hardening, Cardiac, Image Registration, Known Components, MBIR, Metal Artifacts},
pubstate = {published},
tppubtype = {inproceedings}
}
Xu, Shiyu; Khanna, A. Jay; Siewerdsen, Jeffrey H.; Stayman, J. Webster
Polyenergetic known-component CT reconstruction with unknown material compositions and unknown x-ray spectra Journal Article
In: Physics in Medicine and Biology, vol. 62, no. 8, pp. 3352-3374, 2017.
Links | BibTeX | Tags: Artifact Correction, Beam Hardening, Known Components, Metal Artifacts
@article{Xu2017,
title = {Polyenergetic known-component CT reconstruction with unknown material compositions and unknown x-ray spectra},
author = {Shiyu Xu and A. Jay Khanna and Jeffrey H. Siewerdsen and J. Webster Stayman},
url = {https://www.ncbi.nlm.nih.gov/pubmed/28230539
http://iopscience.iop.org/article/10.1088/1361-6560/aa6285/meta},
doi = {10.1088/1361-6560/aa6285},
year = {2017},
date = {2017-02-23},
journal = {Physics in Medicine and Biology},
volume = {62},
number = {8},
pages = {3352-3374},
keywords = {Artifact Correction, Beam Hardening, Known Components, Metal Artifacts},
pubstate = {published},
tppubtype = {article}
}
2014
Stayman, J. Webster; Tilley, Steven; Siewerdsen, Jeffrey H.
Integration of Component Knowledge in Penalized-Likelihood Reconstruction with Morphological and Spectral Uncertainties Proceedings Article
In: Conference proceedings/International Conference on Image Formation in X-Ray Computed Tomography. International Conference on Image Formation in X-Ray Computed Tomography, pp. 111, NIH Public Access 2014.
Links | BibTeX | Tags: Artifact Correction, Known Components, MBIR, Metal Artifacts
@inproceedings{stayman2014integration,
title = {Integration of Component Knowledge in Penalized-Likelihood Reconstruction with Morphological and Spectral Uncertainties},
author = {J. Webster Stayman and Steven Tilley and Jeffrey H. Siewerdsen },
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4211110/},
year = {2014},
date = {2014-01-01},
booktitle = {Conference proceedings/International Conference on Image Formation in X-Ray Computed Tomography. International Conference on Image Formation in X-Ray Computed Tomography},
volume = {2014},
pages = {111},
organization = {NIH Public Access},
keywords = {Artifact Correction, Known Components, MBIR, Metal Artifacts},
pubstate = {published},
tppubtype = {inproceedings}
}
2013
Stayman, J. Webster; Dang, Hao; Otake, Yoshito; Zbijewski, Wojciech; Noble, Jack; Dawant, Benoit; Labadie, Robert; Carey, John P.; Siewerdsen, Jeffrey H.
Overcoming nonlinear partial volume effects in known-component reconstruction of Cochlear implants Proceedings Article
In: Nishikawa, Robert M.; Whiting, Bruce R. (Ed.): SPIE Medical Imaging, pp. 86681L, International Society for Optics and Photonics 2013.
Links | BibTeX | Tags: Artifact Correction, Head/Neck, High-Resolution CT, Known Components, MBIR, Metal Artifacts
@inproceedings{stayman2013overcoming,
title = {Overcoming nonlinear partial volume effects in known-component reconstruction of Cochlear implants},
author = {J. Webster Stayman and Hao Dang and Yoshito Otake and Wojciech Zbijewski and Jack Noble and Benoit Dawant and Robert Labadie and John P. Carey and Jeffrey H. Siewerdsen},
editor = {Robert M. Nishikawa and Bruce R. Whiting },
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4060628/},
doi = {10.1117/12.2007945},
year = {2013},
date = {2013-03-01},
booktitle = {SPIE Medical Imaging},
pages = {86681L},
organization = {International Society for Optics and Photonics},
keywords = {Artifact Correction, Head/Neck, High-Resolution CT, Known Components, MBIR, Metal Artifacts},
pubstate = {published},
tppubtype = {inproceedings}
}
Otake, Yoshito; Stayman, J. Webster; Zbijewski, Wojciech; Murphy, Ryan J.; Kutzer, Michael D.; Taylor, Russell H.; Siewerdsen, Jeffrey H.; Armand, Mehran
Model-based cone-beam CT reconstruction for image-guided minimally invasive treatment of hip osteolysis Proceedings Article
In: III, David R. Holmes; Yaniv, Ziv R. (Ed.): SPIE Medical Imaging, pp. 86710Y, International Society for Optics and Photonics 2013.
Links | BibTeX | Tags: Artifact Correction, Image Guided Surgery, Known Components, MBIR, Metal Artifacts
@inproceedings{otake2013model,
title = {Model-based cone-beam CT reconstruction for image-guided minimally invasive treatment of hip osteolysis},
author = {Yoshito Otake and J. Webster Stayman and Wojciech Zbijewski and Ryan J. Murphy and Michael D. Kutzer and Russell H. Taylor and Jeffrey H. Siewerdsen and Mehran Armand},
editor = {David R. Holmes III and Ziv R. Yaniv },
url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2008094},
doi = {10.1117/12.2008094},
year = {2013},
date = {2013-03-01},
booktitle = {SPIE Medical Imaging},
pages = {86710Y},
organization = {International Society for Optics and Photonics},
keywords = {Artifact Correction, Image Guided Surgery, Known Components, MBIR, Metal Artifacts},
pubstate = {published},
tppubtype = {inproceedings}
}
2012
Stayman, J. Webster; Otake, Yoshito; Prince, Jerry L.; Khanna, A. Jay; Siewerdsen, Jeffrey H.
Model-based tomographic reconstruction of objects containing known components. Journal Article
In: IEEE transactions on medical imaging, vol. 31, no. 10, pp. 1837–48, 2012, ISSN: 1558-254X.
Abstract | Links | BibTeX | Tags: Artifact Correction, Image Registration, Known Components, MBIR, Metal Artifacts, Spine
@article{Stayman2012a,
title = {Model-based tomographic reconstruction of objects containing known components.},
author = {J. Webster Stayman and Yoshito Otake and Jerry L. Prince and A. Jay Khanna and Jeffrey H. Siewerdsen},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4503263},
doi = {10.1109/TMI.2012.2199763},
issn = {1558-254X},
year = {2012},
date = {2012-10-01},
journal = {IEEE transactions on medical imaging},
volume = {31},
number = {10},
pages = {1837--48},
abstract = {The likelihood of finding manufactured components (surgical tools, implants, etc.) within a tomographic field-of-view has been steadily increasing. One reason is the aging population and proliferation of prosthetic devices, such that more people undergoing diagnostic imaging have existing implants, particularly hip and knee implants. Another reason is that use of intraoperative imaging (e.g., cone-beam CT) for surgical guidance is increasing, wherein surgical tools and devices such as screws and plates are placed within or near to the target anatomy. When these components contain metal, the reconstructed volumes are likely to contain severe artifacts that adversely affect the image quality in tissues both near and far from the component. Because physical models of such components exist, there is a unique opportunity to integrate this knowledge into the reconstruction algorithm to reduce these artifacts. We present a model-based penalized-likelihood estimation approach that explicitly incorporates known information about component geometry and composition. The approach uses an alternating maximization method that jointly estimates the anatomy and the position and pose of each of the known components. We demonstrate that the proposed method can produce nearly artifact-free images even near the boundary of a metal implant in simulated vertebral pedicle screw reconstructions and even under conditions of substantial photon starvation. The simultaneous estimation of device pose also provides quantitative information on device placement that could be valuable to quality assurance and verification of treatment delivery.},
keywords = {Artifact Correction, Image Registration, Known Components, MBIR, Metal Artifacts, Spine},
pubstate = {published},
tppubtype = {article}
}
Stayman, J. Webster; Otake, Yoshito; Schafer, Sebastian; Khanna, A. Jay; Prince, Jerry L.; Siewerdsen, Jeffrey H.
Model-based reconstruction of objects with inexactly known components Proceedings Article
In: Pelc, Norbert J.; Nishikawa, Robert M.; Whiting, Bruce R. (Ed.): SPIE Medical Imaging, pp. 83131S, 2012, ISSN: 0277-786X.
Abstract | Links | BibTeX | Tags: Artifact Correction, Image Registration, Known Components, MBIR, Metal Artifacts
@inproceedings{Stayman2012,
title = {Model-based reconstruction of objects with inexactly known components},
author = {J. Webster Stayman and Yoshito Otake and Sebastian Schafer and A. Jay Khanna and Jerry L. Prince and Jeffrey H. Siewerdsen },
editor = {Norbert J. Pelc and Robert M. Nishikawa and Bruce R. Whiting },
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4507268},
doi = {10.1117/12.911202},
issn = {0277-786X},
year = {2012},
date = {2012-02-01},
booktitle = {SPIE Medical Imaging},
volume = {8313},
number = {10},
pages = {83131S},
abstract = {Because tomographic reconstructions are ill-conditioned, algorithms that incorporate additional knowledge about the imaging volume generally have improved image quality. This is particularly true when measurements are noisy or have missing data. This paper presents a general reconstruction framework for including attenuation contributions from objects known to be in the field-of-view. Components such as surgical devices and tools may be modeled explicitly as part of the attenuating volume but are inexactly known with respect to their locations poses, and possible deformations. The proposed reconstruction framework, referred to as Known-Component Reconstruction (KCR), is based on this novel parameterization of the object, a likelihood-based objective function, and alternating optimizations between registration and image parameters to jointly estimate the both the underlying attenuation and unknown registrations. A deformable KCR (dKCR) approach is introduced that adopts a control point-based warping operator to accommodate shape mismatches between the component model and the physical component, thereby allowing for a more general class of inexactly known components. The KCR and dKCR approaches are applied to low-dose cone-beam CT data with spine fixation hardware present in the imaging volume. Such data is particularly challenging due to photon starvation effects in projection data behind the metallic components. The proposed algorithms are compared with traditional filtered-backprojection and penalized-likelihood reconstructions and found to provide substantially improved image quality. Whereas traditional approaches exhibit significant artifacts that complicate detection of breaches or fractures near metal, the KCR framework tends to provide good visualization of anatomy right up to the boundary of surgical devices.},
keywords = {Artifact Correction, Image Registration, Known Components, MBIR, Metal Artifacts},
pubstate = {published},
tppubtype = {inproceedings}
}
Zbijewski, Wojciech; Stayman, J. Webster; Muhit, Abdullah Al; Yorkston, John; Carrino, John A.; Siewerdsen, Jeffrey H.
CT Reconstruction Using Spectral and Morphological Prior Knowledge: Application to Imaging the Prosthetic Knee Proceedings Article
In: Second Int. Conf. Image Form. X-ray Computed Tomography, pp. 434–438, 2012.
Links | BibTeX | Tags: Artifact Correction, Beam Hardening, Extremities, Known Components, MBIR, Metal Artifacts, Spectral X-ray/CT
@inproceedings{Zbijewski2012,
title = {CT Reconstruction Using Spectral and Morphological Prior Knowledge: Application to Imaging the Prosthetic Knee},
author = {Wojciech Zbijewski and J. Webster Stayman and Abdullah Al Muhit and John Yorkston and John A. Carrino and Jeffrey H. Siewerdsen },
url = {http://istar.jhu.edu/pdf/Zbijewski_KCR_CTMeeting2012.pdf},
year = {2012},
date = {2012-01-01},
booktitle = {Second Int. Conf. Image Form. X-ray Computed Tomography},
pages = {434--438},
keywords = {Artifact Correction, Beam Hardening, Extremities, Known Components, MBIR, Metal Artifacts, Spectral X-ray/CT},
pubstate = {published},
tppubtype = {inproceedings}
}