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Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial. Moult, Eric; Burdette, Everette Clif; Song, Danny Y.; Abolmaesumi, Purang; Fichtinger, Gabor; Fallavollita, Pascal
Abstract
Motivation: In prostate brachytherapy, real-time dosimetry would be ideal to allow for rapid evaluation of the implant quality intra-operatively. However, such a mechanism requires an imaging system that is both real-time and which provides, via multiple C-arm fluoroscopy images, clear information describing the three-dimensional position of the seeds deposited within the prostate. Thus, accurate tracking of the C-arm poses proves to be of critical importance to the process. Methodology: We compute the pose of the C-arm relative to a stationary radiographic fiducial of known geometry by employing a hybrid registration framework. Firstly, by means of an ellipse segmentation algorithm and a 2D/3D feature based registration, we exploit known FTRAC geometry to recover an initial estimate of the C-arm pose. Using this estimate, we then initialize the intensity-based registration which serves to recover a refined and accurate estimation of the C-arm pose. Results: Ground-truth pose was established for each C-arm image through a published and clinically tested segmentation-based method. Using 169 clinical C-arm images and a ±10° and ±10 mm random perturbation of the ground-truth pose, the average rotation and translation errors were 0.68° (std = 0.06°) and 0.64 mm (std = 0.24 mm). Conclusion: Fully automated C-arm pose estimation using a 2D/3D hybrid registration scheme was found to be clinically robust based on human patient data. Copyright 2011 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Item Metadata
Title |
Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial.
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Creator | |
Publisher |
Society of Photo-Optical Instrumentation Engineers (SPIE)
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Date Issued |
2011
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Description |
Motivation: In prostate brachytherapy, real-time dosimetry would be ideal to allow for rapid evaluation of the implant quality intra-operatively. However,
such a mechanism requires an imaging system that is both real-time and which provides, via multiple C-arm fluoroscopy images, clear information describing
the three-dimensional position of the seeds deposited within the prostate. Thus, accurate tracking of the C-arm poses proves to be of critical importance
to the process. Methodology: We compute the pose of the C-arm relative to a stationary radiographic fiducial of known geometry by employing a hybrid
registration framework. Firstly, by means of an ellipse segmentation algorithm and a 2D/3D feature based registration, we exploit known FTRAC geometry to
recover an initial estimate of the C-arm pose. Using this estimate, we then initialize the intensity-based registration which serves to recover a refined
and accurate estimation of the C-arm pose. Results: Ground-truth pose was established for each C-arm image through a published and clinically tested
segmentation-based method. Using 169 clinical C-arm images and a ±10° and ±10 mm random perturbation of the ground-truth pose, the average rotation and
translation errors were 0.68° (std = 0.06°) and 0.64 mm (std = 0.24 mm). Conclusion: Fully automated C-arm pose estimation using a 2D/3D hybrid registration
scheme was found to be clinically robust based on human patient data.
Copyright 2011 Society of Photo-Optical Instrumentation Engineers.
One print or electronic copy may be made for personal use only. Systematic reproduction and distribution,
duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
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Genre | |
Type | |
Language |
eng
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Date Available |
2011-08-16
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0107558
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URI | |
Affiliation | |
Citation |
Moult, Eric: Burdette, Everette Clif; Song, Danny Y.; Abolmaesumi, Purang; Fichtinger, Gabor; Fallavollita, Pascal; Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial. Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, edited by Kenneth H. Wong, David R. Holmes III, Proceedings of SPIE, Volume 7964, 79642S, 2011.
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Publisher DOI |
10.1117/12.877713
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty
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Copyright Holder |
Abolmaesumi, Purang
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International