The Experts below are selected from a list of 34230 Experts worldwide ranked by ideXlab platform
Joachim E. Zöller - One of the best experts on this subject based on the ideXlab platform.
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Registration Accuracy of three dimensional surface and cone beam computed tomography data for virtual implant planning
Clinical Oral Implants Research, 2012Co-Authors: Lutz Ritter, S. D. Reiz, Daniel Rothamel, Timo Dreiseidler, V. E. Karapetian, M. Scheer, Joachim E. ZöllerAbstract:Objective: Virtual wax-ups based on three-dimensional (3D) surface models can be matched (i.e. registered) to cone beam computed tomography (CBCT) data of the same patient for dental implant planning. Thereby, implant planning software can visualize anatomical and prosthetic information simultaneously. The aim of this study is to assess the Accuracy of a newly developed Registration process. Material and methods: Data pairs of CBCT and 3D surface data of 16 patients for dental implant planning were registered and the discrepancy between the visualized 3D surface data and the corresponding CBCT data were measured on 64 teeth at seven points by two investigators in two iterations with a total of 1792 measurements. Results: All data pairs were matched successfully and mean distances between CBCT and 3D surface data were between 0.03(±0.33) and 0.14(±0.18) mm. At two of seven measuring points, statistically significant correlations were determined between the measured error and the presence and type of restorations. Registration errors in maxilla and mandible were not statistically significantly different. Conclusion: According to the results of this study, Registration of 3D surface data and CBCT data works reliably and is sufficiently accurate for dental implant planning. Thereby, barium-sulfate scanning templates can be avoided and dental implant planning can be accomplished fully virtual. To cite this article: Ritter L, Reiz SD, Rothamel D, Dreiseidler T, Karapetian V, Scheer M, Zoller JE. Registration Accuracy of three-dimensional surface and cone beam computed tomography data for virtual implant planning. Clin. Oral Impl. Res. 23, 2012 447–452. doi: 10.1111/j.1600-0501.2011.02159.x
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Registration Accuracy of three‐dimensional surface and cone beam computed tomography data for virtual implant planning
Clinical oral implants research, 2011Co-Authors: Lutz Ritter, S. D. Reiz, Daniel Rothamel, Timo Dreiseidler, V. E. Karapetian, M. Scheer, Joachim E. ZöllerAbstract:Objective: Virtual wax-ups based on three-dimensional (3D) surface models can be matched (i.e. registered) to cone beam computed tomography (CBCT) data of the same patient for dental implant planning. Thereby, implant planning software can visualize anatomical and prosthetic information simultaneously. The aim of this study is to assess the Accuracy of a newly developed Registration process. Material and methods: Data pairs of CBCT and 3D surface data of 16 patients for dental implant planning were registered and the discrepancy between the visualized 3D surface data and the corresponding CBCT data were measured on 64 teeth at seven points by two investigators in two iterations with a total of 1792 measurements. Results: All data pairs were matched successfully and mean distances between CBCT and 3D surface data were between 0.03(±0.33) and 0.14(±0.18) mm. At two of seven measuring points, statistically significant correlations were determined between the measured error and the presence and type of restorations. Registration errors in maxilla and mandible were not statistically significantly different. Conclusion: According to the results of this study, Registration of 3D surface data and CBCT data works reliably and is sufficiently accurate for dental implant planning. Thereby, barium-sulfate scanning templates can be avoided and dental implant planning can be accomplished fully virtual. To cite this article: Ritter L, Reiz SD, Rothamel D, Dreiseidler T, Karapetian V, Scheer M, Zoller JE. Registration Accuracy of three-dimensional surface and cone beam computed tomography data for virtual implant planning. Clin. Oral Impl. Res. 23, 2012 447–452. doi: 10.1111/j.1600-0501.2011.02159.x
J Williamson - One of the best experts on this subject based on the ideXlab platform.
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SU‐FF‐J‐170: Impact of 4D Cone Beam CT View‐Aliasing Artifact On Nonrigid Registration Accuracy
Medical Physics, 2009Co-Authors: Geoffrey D. Hugo, W. Sleeman, J WilliamsonAbstract:Purpose: To evaluate the effect of 4D cone beam CT view‐aliasing artifact on nonrigid Registration Accuracy. Method and Materials: End exhalation (EE) and end inhalation (EI) volumes from a 4D multi‐slice CTimage (4DCT) of a research subject were registered using a small deformation inverse consistent linear elastic (SICLE) Registration algorithm to produce a reference displacement vector field (DVF) between the two images. Artificial cone beam CT projections were generated for the EE and EI volumes at several different angular sampling patterns, mimicking 4D cone beam CT (4DCBCT) acquisition in a free‐breathing patient. The projections were reconstructed into EE and EI 4DCBCT phase images containing view‐aliasing artifact due to angular undersampling, but without CBCT scatter and beam hardening artifacts. The EE and EI 4DCBCT images were registered using the SICLE algorithm to produce a test DVF. Test DVFs were generated at a range of angular frequencies from 0.17 projections per degree to 1.83 projections per degree (full angular sampling on a commercial cone beam CT system). The norm of the voxel by voxel vector difference between the test DVF and reference DVF within the patient's delineated lung volume was calculated. Results: The mean absolute error was significantly associated with the projection angular frequency (p < 0.05, exponential regression, R2=0.996). The median error was below 0.2 cm and 90% of the error was below 0.3 cm for the lowest frequency evaluated here of 60 projections per phase. However, above a sampling frequency of 0.33 projections per degree (120 projections per phase), 90% of the error was less than 0.1 cm in relation to the 4DCT Registration. Conclusion: Using at least 120 projections per phase, view‐aliasing artifact had a minimal effect on the Registration Accuracy for the SICLE algorithm due to inherent elastic and smoothing constraints in the algorithm.
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su ff j 170 impact of 4d cone beam ct view aliasing artifact on nonrigid Registration Accuracy
Medical Physics, 2009Co-Authors: G Hugo, W. Sleeman, J WilliamsonAbstract:Purpose: To evaluate the effect of 4D cone beam CT view‐aliasing artifact on nonrigid Registration Accuracy. Method and Materials: End exhalation (EE) and end inhalation (EI) volumes from a 4D multi‐slice CTimage (4DCT) of a research subject were registered using a small deformation inverse consistent linear elastic (SICLE) Registration algorithm to produce a reference displacement vector field (DVF) between the two images. Artificial cone beam CT projections were generated for the EE and EI volumes at several different angular sampling patterns, mimicking 4D cone beam CT (4DCBCT) acquisition in a free‐breathing patient. The projections were reconstructed into EE and EI 4DCBCT phase images containing view‐aliasing artifact due to angular undersampling, but without CBCT scatter and beam hardening artifacts. The EE and EI 4DCBCT images were registered using the SICLE algorithm to produce a test DVF. Test DVFs were generated at a range of angular frequencies from 0.17 projections per degree to 1.83 projections per degree (full angular sampling on a commercial cone beam CT system). The norm of the voxel by voxel vector difference between the test DVF and reference DVF within the patient's delineated lung volume was calculated. Results: The mean absolute error was significantly associated with the projection angular frequency (p < 0.05, exponential regression, R2=0.996). The median error was below 0.2 cm and 90% of the error was below 0.3 cm for the lowest frequency evaluated here of 60 projections per phase. However, above a sampling frequency of 0.33 projections per degree (120 projections per phase), 90% of the error was less than 0.1 cm in relation to the 4DCT Registration. Conclusion: Using at least 120 projections per phase, view‐aliasing artifact had a minimal effect on the Registration Accuracy for the SICLE algorithm due to inherent elastic and smoothing constraints in the algorithm.
Jeffrey H. Siewerdsen - One of the best experts on this subject based on the ideXlab platform.
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Effects of Image Quality on the Fundamental Limits of Image Registration Accuracy
IEEE Transactions on Medical Imaging, 2017Co-Authors: Michael D. Ketcha, Tharindu De Silva, Ali Uneri, Joseph Goerres, Matthew W. Jacobson, Sebastian Vogt, Gerhard Kleinszig, Jeffrey H. SiewerdsenAbstract:For image-guided procedures, the imaging task is often tied to the Registration of intraoperative and preoperative images to a common coordinate system. While the Accuracy of this Registration is a vital factor in system performance, there is a relatively little work that relates Registration Accuracy to image quality factors, such as dose, noise, and spatial resolution. To create a theoretical model for such a relationship, we present a Fisher information approach to analyze Registration performance in explicit dependence on the underlying image quality factors of image noise, spatial resolution, and signal power spectrum. The model yields analysis of the Cramer-Rao lower bound (CRLB), in Registration Accuracy as a function of factors governing image quality. Experiments were performed in simulation of computed tomography low-contrast soft tissue images and high-contrast bone (head and neck) images to compare the measured Accuracy [root mean squared error (RMSE) of the estimated transformations] with the theoretical lower bound. Analysis of the CRLB reveals that Registration performance is closely related to the signal-to-noise ratio of the cross-correlation space. While the lower bound is optimistic, it exhibits consistent trends with experimental findings and yields a method for comparing the performance of various Registration methods and similarity metrics. Further analysis validated a method for determining optimal post-processing (image filtering) for Registration. Two figures of merit (CRLB and RMSE) are presented that unify models of image quality with Registration performance, providing an important guide to optimizing intraoperative imaging with respect to the task of Registration.
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3d 2d Registration for surgical guidance effect of projection view angles on Registration Accuracy
Physics in Medicine and Biology, 2014Co-Authors: A Uneri, Sebastian Vogt, Gerhard Kleinszig, Yoshito Otake, Adam S. Wang, A. J. Khanna, Jeffrey H. SiewerdsenAbstract:An algorithm for intensity-based 3D–2D Registration of CT and x-ray projections is evaluated, specifically using single- or dual-projection views to provide 3D localization. The Registration framework employs the gradient information similarity metric and covariance matrix adaptation evolution strategy to solve for the patient pose in six degrees of freedom. Registration performance was evaluated in an anthropomorphic phantom and cadaver, using C-arm projection views acquired at angular separation, Δθ, ranging from ~0°–180° at variable C-arm magnification. Registration Accuracy was assessed in terms of 2D projection distance error and 3D target Registration error (TRE) and compared to that of an electromagnetic (EM) tracker. The results indicate that angular separation as small as Δθ ~10°–20° achieved TRE <2 mm with 95% confidence, comparable or superior to that of the EM tracker. The method allows direct Registration of preoperative CT and planning data to intraoperative fluoroscopy, providing 3D localization free from conventional limitations associated with external fiducial markers, stereotactic frames, trackers and manual Registration.
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3D–2D Registration for surgical guidance: effect of projection view angles on Registration Accuracy
Physics in medicine and biology, 2013Co-Authors: Ali Uneri, Sebastian Vogt, Gerhard Kleinszig, Yoshito Otake, Adam S. Wang, A. J. Khanna, Jeffrey H. SiewerdsenAbstract:An algorithm for intensity-based 3D–2D Registration of CT and x-ray projections is evaluated, specifically using single- or dual-projection views to provide 3D localization. The Registration framework employs the gradient information similarity metric and covariance matrix adaptation evolution strategy to solve for the patient pose in six degrees of freedom. Registration performance was evaluated in an anthropomorphic phantom and cadaver, using C-arm projection views acquired at angular separation, Δθ, ranging from ~0°–180° at variable C-arm magnification. Registration Accuracy was assessed in terms of 2D projection distance error and 3D target Registration error (TRE) and compared to that of an electromagnetic (EM) tracker. The results indicate that angular separation as small as Δθ ~10°–20° achieved TRE
Lutz Ritter - One of the best experts on this subject based on the ideXlab platform.
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Registration Accuracy of three dimensional surface and cone beam computed tomography data for virtual implant planning
Clinical Oral Implants Research, 2012Co-Authors: Lutz Ritter, S. D. Reiz, Daniel Rothamel, Timo Dreiseidler, V. E. Karapetian, M. Scheer, Joachim E. ZöllerAbstract:Objective: Virtual wax-ups based on three-dimensional (3D) surface models can be matched (i.e. registered) to cone beam computed tomography (CBCT) data of the same patient for dental implant planning. Thereby, implant planning software can visualize anatomical and prosthetic information simultaneously. The aim of this study is to assess the Accuracy of a newly developed Registration process. Material and methods: Data pairs of CBCT and 3D surface data of 16 patients for dental implant planning were registered and the discrepancy between the visualized 3D surface data and the corresponding CBCT data were measured on 64 teeth at seven points by two investigators in two iterations with a total of 1792 measurements. Results: All data pairs were matched successfully and mean distances between CBCT and 3D surface data were between 0.03(±0.33) and 0.14(±0.18) mm. At two of seven measuring points, statistically significant correlations were determined between the measured error and the presence and type of restorations. Registration errors in maxilla and mandible were not statistically significantly different. Conclusion: According to the results of this study, Registration of 3D surface data and CBCT data works reliably and is sufficiently accurate for dental implant planning. Thereby, barium-sulfate scanning templates can be avoided and dental implant planning can be accomplished fully virtual. To cite this article: Ritter L, Reiz SD, Rothamel D, Dreiseidler T, Karapetian V, Scheer M, Zoller JE. Registration Accuracy of three-dimensional surface and cone beam computed tomography data for virtual implant planning. Clin. Oral Impl. Res. 23, 2012 447–452. doi: 10.1111/j.1600-0501.2011.02159.x
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Registration Accuracy of three‐dimensional surface and cone beam computed tomography data for virtual implant planning
Clinical oral implants research, 2011Co-Authors: Lutz Ritter, S. D. Reiz, Daniel Rothamel, Timo Dreiseidler, V. E. Karapetian, M. Scheer, Joachim E. ZöllerAbstract:Objective: Virtual wax-ups based on three-dimensional (3D) surface models can be matched (i.e. registered) to cone beam computed tomography (CBCT) data of the same patient for dental implant planning. Thereby, implant planning software can visualize anatomical and prosthetic information simultaneously. The aim of this study is to assess the Accuracy of a newly developed Registration process. Material and methods: Data pairs of CBCT and 3D surface data of 16 patients for dental implant planning were registered and the discrepancy between the visualized 3D surface data and the corresponding CBCT data were measured on 64 teeth at seven points by two investigators in two iterations with a total of 1792 measurements. Results: All data pairs were matched successfully and mean distances between CBCT and 3D surface data were between 0.03(±0.33) and 0.14(±0.18) mm. At two of seven measuring points, statistically significant correlations were determined between the measured error and the presence and type of restorations. Registration errors in maxilla and mandible were not statistically significantly different. Conclusion: According to the results of this study, Registration of 3D surface data and CBCT data works reliably and is sufficiently accurate for dental implant planning. Thereby, barium-sulfate scanning templates can be avoided and dental implant planning can be accomplished fully virtual. To cite this article: Ritter L, Reiz SD, Rothamel D, Dreiseidler T, Karapetian V, Scheer M, Zoller JE. Registration Accuracy of three-dimensional surface and cone beam computed tomography data for virtual implant planning. Clin. Oral Impl. Res. 23, 2012 447–452. doi: 10.1111/j.1600-0501.2011.02159.x
Takeo Kanade - One of the best experts on this subject based on the ideXlab platform.
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geometric constraint analysis and synthesis methods for improving shape based Registration Accuracy
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision Virtual Reality and Robotics in Medicine and Medial Robotics and Compute, 1997Co-Authors: David A Simon, Takeo KanadeAbstract:Shape-based Registration is a process for estimating the transformation between two shape representations of an object. It is used in many image-guided surgical systems to establish a transformation between pre- and intra-operative coordinate systems. This paper describes several tools which are useful for improving the Accuracy resulting from shape-based Registration: constraint analysis, constraint synthesis, and online Accuracy estimation. Constraint analysis provides a scalar measure of sensitivity which is well correlated with Registration Accuracy. This measure can be used as a criterion function by constraint synthesis, an optimization process which generates configurations of Registration data which maximize expected Accuracy. Online Accuracy estimation uses a conventional root-mean-squared error measure coupled with constraint analysis to estimate an upper bound on true Registration error. This paper demonstrates that Registration Accuracy can be significantly improved via application of these methods.
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CVRMed - Geometric constraint analysis and synthesis: methods for improving shape-based Registration Accuracy
Lecture Notes in Computer Science, 1997Co-Authors: David A Simon, Takeo KanadeAbstract:Shape-based Registration is a process for estimating the transformation between two shape representations of an object. It is used in many image-guided surgical systems to establish a transformation between pre- and intra-operative coordinate systems. This paper describes several tools which are useful for improving the Accuracy resulting from shape-based Registration: constraint analysis, constraint synthesis, and online Accuracy estimation. Constraint analysis provides a scalar measure of sensitivity which is well correlated with Registration Accuracy. This measure can be used as a criterion function by constraint synthesis, an optimization process which generates configurations of Registration data which maximize expected Accuracy. Online Accuracy estimation uses a conventional root-mean-squared error measure coupled with constraint analysis to estimate an upper bound on true Registration error. This paper demonstrates that Registration Accuracy can be significantly improved via application of these methods.
