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In‐vitro assessment of a registration protocol for image guided implant dentistry

Identifieur interne : 004841 ( Istex/Corpus ); précédent : 004840; suivant : 004842

In‐vitro assessment of a registration protocol for image guided implant dentistry

Auteurs : Wolfgang Birkfellner ; Peter Solar ; André Gahleitner ; Klaus Huber ; Franz Kainberger ; Joachim Kettenbach ; Peter Homolka ; Markus Diemling ; Georg Watzek ; Helmar Bergmann

Source :

RBID : ISTEX:90EAF67B978EA6CE9A8AD70752D3B776998E3EB7

English descriptors

Abstract

Abstract: In this study a computer aided navigation technique for accurate positioning of oral implants was assessed. An optical tracking system with specially designed tools for monitoring the position of surgical instruments relative to the patient was used to register 5 partially or completely edentulous jaw models. Besides the accuracy of the tracking system, the precision of localizing a specific position on 3‐dimensional preoperative imagery is governed by the registration algorithm which conveys the co‐ordinate system of the preoperative computed tomography (CT) scan to the actual patient position. Two different point‐to‐point registration algorithms were compared for their suitability for this application. The accuracy was determined separately for the localization error of the position measurement hardware (fiducial localization error – FLE) and the error as reported by the registration algorithm (fiducial registration error – FRE). The overall error of the navigation procedure was determined as the localization error of additional landmarks (steel spheres, 0.5 mm diameter) after registration (target registration error – TRE). Images of the jaw models were obtained using a high resolution CT scan (1.5 mm slice thickness, 1 mm table feed, incremental scanning, 120 kV, 150 mAs, 512 · 512 matrix, FOV 120 mm). The accuracy of the position measurement probes was 0.69±0.15 mm (FLE). Using 3 implanted fiducial markers, FRE was 0.71±0.12 mm on average and 1.00±0.13 mm maximum. TRE was found to be 1.23±0.28 mm average and 1.87±0.47 mm maximum. Increasing the number of fiducial markers to a total of 5 did not significantly improve precision. Furthermore it was found that a registration algorithm based on solving an eigenvalue problem is the superior approach for point‐to‐point matching in terms of mathematical stability. The experimental results indicate that positioning accuracy of oral implants may benefit from computer aided intraoperative navigation. The accuracy achieved compares well to the resolution of the CT scan used. Further development of point‐to‐point/point‐to‐surface registration methods and tracking hardware has the potential to improve the precision of the method even further. Our system has potential to reduce the intraoperative risk of causing damage to critical anatomic structures, to minimize the efforts in prosthetic modelling, and to simplify the task of transferring preoperative planning data precisely to the operating room in general.

Url:
DOI: 10.1034/j.1600-0501.2001.012001069.x

Links to Exploration step

ISTEX:90EAF67B978EA6CE9A8AD70752D3B776998E3EB7

Le document en format XML

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assessment of a registration protocol for image guided implant dentistry</title>
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<title level="j" type="main">Clinical Oral Implants Research</title>
<title level="j" type="alt">CLINICAL ORAL IMPLANTS RESEARCH</title>
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<term>Biomedical engineering</term>
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<term>Clin</term>
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<term>Clinical applications</term>
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<term>Dental drill</term>
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<term>Dentistry</term>
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<term>Ducial localization error</term>
<term>Ducial marker</term>
<term>Ducial marker positions</term>
<term>Ducial markers</term>
<term>Ducial registration error</term>
<term>Edentulous</term>
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<term>Eigenvalue problem</term>
<term>Fiducial registration error</term>
<term>Fitzpatrick</term>
<term>General hospital vienna</term>
<term>Head diameter</term>
<term>High resolution</term>
<term>Ieee</term>
<term>Ieee trans</term>
<term>Ieee transactions</term>
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<term>Imaging</term>
<term>Imaging techniques</term>
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<term>Implant</term>
<term>Implant dentistry</term>
<term>Implant drill</term>
<term>Implant placement</term>
<term>Implant position</term>
<term>Implant surgery</term>
<term>Implantes orales</term>
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<term>Lavallee</term>
<term>Local anaesthesia</term>
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<term>Localization error</term>
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<term>Marker</term>
<term>Matrix</term>
<term>Maurer</term>
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<term>Mayo clinic</term>
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<term>Reformatted slices</term>
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<term>Registration algorithms</term>
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<term>Slice thickness</term>
<term>Small size</term>
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<term>Table feed</term>
<term>Target registration error</term>
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<term>Biomedical imaging resource</term>
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<term>Clinical applicability</term>
<term>Clinical applications</term>
<term>Data acquisition</term>
<term>Dental drill</term>
<term>Dental implants</term>
<term>Dentistry</term>
<term>Different registration algorithms</term>
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<term>Imaging techniques</term>
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<term>Implant dentistry</term>
<term>Implant drill</term>
<term>Implant placement</term>
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<term>Maximal values</term>
<term>Mayo clinic</term>
<term>Medical imaging</term>
<term>Molar</term>
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<term>Navigation system</term>
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<term>Oblique reformatting</term>
<term>Optical tracker</term>
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<term>Oral implants</term>
<term>Overall error</term>
<term>Physical space</term>
<term>Position data</term>
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<term>Preoperative imagery</term>
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<term>Reference probe</term>
<term>Reformatted slices</term>
<term>Registration algorithm</term>
<term>Registration algorithms</term>
<term>Registration error</term>
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<term>Registration transformation</term>
<term>Reliable registration</term>
<term>Rotation matrix</term>
<term>Screw heads</term>
<term>Single point measurements</term>
<term>Slice thickness</term>
<term>Small size</term>
<term>Splint</term>
<term>Standard deviation</term>
<term>Steel spheres</term>
<term>Surface points</term>
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<term>Target registration error</term>
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<term>Thin arrows</term>
<term>Tional journal</term>
<term>Tracker</term>
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<front>
<div type="abstract">Abstract: In this study a computer aided navigation technique for accurate positioning of oral implants was assessed. An optical tracking system with specially designed tools for monitoring the position of surgical instruments relative to the patient was used to register 5 partially or completely edentulous jaw models. Besides the accuracy of the tracking system, the precision of localizing a specific position on 3‐dimensional preoperative imagery is governed by the registration algorithm which conveys the co‐ordinate system of the preoperative computed tomography (CT) scan to the actual patient position. Two different point‐to‐point registration algorithms were compared for their suitability for this application. The accuracy was determined separately for the localization error of the position measurement hardware (fiducial localization error – FLE) and the error as reported by the registration algorithm (fiducial registration error – FRE). The overall error of the navigation procedure was determined as the localization error of additional landmarks (steel spheres, 0.5 mm diameter) after registration (target registration error – TRE). Images of the jaw models were obtained using a high resolution CT scan (1.5 mm slice thickness, 1 mm table feed, incremental scanning, 120 kV, 150 mAs, 512 · 512 matrix, FOV 120 mm). The accuracy of the position measurement probes was 0.69±0.15 mm (FLE). Using 3 implanted fiducial markers, FRE was 0.71±0.12 mm on average and 1.00±0.13 mm maximum. TRE was found to be 1.23±0.28 mm average and 1.87±0.47 mm maximum. Increasing the number of fiducial markers to a total of 5 did not significantly improve precision. Furthermore it was found that a registration algorithm based on solving an eigenvalue problem is the superior approach for point‐to‐point matching in terms of mathematical stability. The experimental results indicate that positioning accuracy of oral implants may benefit from computer aided intraoperative navigation. The accuracy achieved compares well to the resolution of the CT scan used. Further development of point‐to‐point/point‐to‐surface registration methods and tracking hardware has the potential to improve the precision of the method even further. Our system has potential to reduce the intraoperative risk of causing damage to critical anatomic structures, to minimize the efforts in prosthetic modelling, and to simplify the task of transferring preoperative planning data precisely to the operating room in general.</div>
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<name>Markus Diemling</name>
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<abstract>Abstract: In this study a computer aided navigation technique for accurate positioning of oral implants was assessed. An optical tracking system with specially designed tools for monitoring the position of surgical instruments relative to the patient was used to register 5 partially or completely edentulous jaw models. Besides the accuracy of the tracking system, the precision of localizing a specific position on 3‐dimensional preoperative imagery is governed by the registration algorithm which conveys the co‐ordinate system of the preoperative computed tomography (CT) scan to the actual patient position. Two different point‐to‐point registration algorithms were compared for their suitability for this application. The accuracy was determined separately for the localization error of the position measurement hardware (fiducial localization error – FLE) and the error as reported by the registration algorithm (fiducial registration error – FRE). The overall error of the navigation procedure was determined as the localization error of additional landmarks (steel spheres, 0.5 mm diameter) after registration (target registration error – TRE). Images of the jaw models were obtained using a high resolution CT scan (1.5 mm slice thickness, 1 mm table feed, incremental scanning, 120 kV, 150 mAs, 512 · 512 matrix, FOV 120 mm). The accuracy of the position measurement probes was 0.69±0.15 mm (FLE). Using 3 implanted fiducial markers, FRE was 0.71±0.12 mm on average and 1.00±0.13 mm maximum. TRE was found to be 1.23±0.28 mm average and 1.87±0.47 mm maximum. Increasing the number of fiducial markers to a total of 5 did not significantly improve precision. Furthermore it was found that a registration algorithm based on solving an eigenvalue problem is the superior approach for point‐to‐point matching in terms of mathematical stability. The experimental results indicate that positioning accuracy of oral implants may benefit from computer aided intraoperative navigation. The accuracy achieved compares well to the resolution of the CT scan used. Further development of point‐to‐point/point‐to‐surface registration methods and tracking hardware has the potential to improve the precision of the method even further. Our system has potential to reduce the intraoperative risk of causing damage to critical anatomic structures, to minimize the efforts in prosthetic modelling, and to simplify the task of transferring preoperative planning data precisely to the operating room in general.</abstract>
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In this study a computer aided navigation technique for accurate positioning of oral implants was assessed. An optical tracking system with specially designed tools for monitoring the position of surgical instruments relative to the patient was used to register 5 partially or completely edentulous jaw models. Besides the accuracy of the tracking system, the precision of localizing a specific position on 3‐dimensional preoperative imagery is governed by the registration algorithm which conveys the co‐ordinate system of the preoperative computed tomography (CT) scan to the actual patient position. Two different point‐to‐point registration algorithms were compared for their suitability for this application. The accuracy was determined separately for the localization error of the position measurement hardware (fiducial localization error – FLE) and the error as reported by the registration algorithm (fiducial registration error – FRE). The overall error of the navigation procedure was determined as the localization error of additional landmarks (steel spheres, 0.5 mm diameter) after registration (target registration error – TRE). Images of the jaw models were obtained using a high resolution CT scan (1.5 mm slice thickness, 1 mm table feed, incremental scanning, 120 kV, 150 mAs, 512 · 512 matrix, FOV 120 mm). The accuracy of the position measurement probes was 0.69±0.15 mm (FLE). Using 3 implanted fiducial markers, FRE was 0.71±0.12 mm on average and 1.00±0.13 mm maximum. TRE was found to be 1.23±0.28 mm average and 1.87±0.47 mm maximum. Increasing the number of fiducial markers to a total of 5 did not significantly improve precision. Furthermore it was found that a registration algorithm based on solving an eigenvalue problem is the superior approach for point‐to‐point matching in terms of mathematical stability. The experimental results indicate that positioning accuracy of oral implants may benefit from computer aided intraoperative navigation. The accuracy achieved compares well to the resolution of the CT scan used. Further development of point‐to‐point/point‐to‐surface registration methods and tracking hardware has the potential to improve the precision of the method even further. Our system has potential to reduce the intraoperative risk of causing damage to critical anatomic structures, to minimize the efforts in prosthetic modelling, and to simplify the task of transferring preoperative planning data precisely to the operating room in general.</p>
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<correspondenceTo> Correspondence to: 

<i>Wolfgang Birkfellner</i>
,
Department of Biomedical Engineering and Physics,
University of Vienna,
General Hospital 4L,
A‐1090 Vienna, Austria
Tel.: +43 1 40 400 3982
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<abstract>Abstract: In this study a computer aided navigation technique for accurate positioning of oral implants was assessed. An optical tracking system with specially designed tools for monitoring the position of surgical instruments relative to the patient was used to register 5 partially or completely edentulous jaw models. Besides the accuracy of the tracking system, the precision of localizing a specific position on 3‐dimensional preoperative imagery is governed by the registration algorithm which conveys the co‐ordinate system of the preoperative computed tomography (CT) scan to the actual patient position. Two different point‐to‐point registration algorithms were compared for their suitability for this application. The accuracy was determined separately for the localization error of the position measurement hardware (fiducial localization error – FLE) and the error as reported by the registration algorithm (fiducial registration error – FRE). The overall error of the navigation procedure was determined as the localization error of additional landmarks (steel spheres, 0.5 mm diameter) after registration (target registration error – TRE). Images of the jaw models were obtained using a high resolution CT scan (1.5 mm slice thickness, 1 mm table feed, incremental scanning, 120 kV, 150 mAs, 512 · 512 matrix, FOV 120 mm). The accuracy of the position measurement probes was 0.69±0.15 mm (FLE). Using 3 implanted fiducial markers, FRE was 0.71±0.12 mm on average and 1.00±0.13 mm maximum. TRE was found to be 1.23±0.28 mm average and 1.87±0.47 mm maximum. Increasing the number of fiducial markers to a total of 5 did not significantly improve precision. Furthermore it was found that a registration algorithm based on solving an eigenvalue problem is the superior approach for point‐to‐point matching in terms of mathematical stability. The experimental results indicate that positioning accuracy of oral implants may benefit from computer aided intraoperative navigation. The accuracy achieved compares well to the resolution of the CT scan used. Further development of point‐to‐point/point‐to‐surface registration methods and tracking hardware has the potential to improve the precision of the method even further. Our system has potential to reduce the intraoperative risk of causing damage to critical anatomic structures, to minimize the efforts in prosthetic modelling, and to simplify the task of transferring preoperative planning data precisely to the operating room in general.</abstract>
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