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Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial.

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Title: Automatic C-arm pose estimation via 2D/3D hybrid registration of a radiographic fiducial.
Author: Moult, Eric; Burdette, Everette Clif; Song, Danny Y.; Abolmaesumi, Purang; Fichtinger, Gabor; Fallavollita, Pascal
Issue Date: 2011
Publicly Available in cIRcle 2011-08-16
Publisher Society of Photo-Optical Instrumentation Engineers
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. http://dx.doi.org/10.1117/12.877713
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.
Affiliation: Applied Science, Faculty ofElectrical and Computer Engineering, Department of
URI: http://hdl.handle.net/2429/36696
Peer Review Status: Reviewed
Scholarly Level: Faculty

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