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The Effects of Distribution of Image Matched Fiducial Markers on Accuracy of Computer‐Guided Implant Surgery
Author(s) -
Choi YongDo,
Mai HangNga,
Mai Hai Yen,
Ha JungHong,
Li LinJie,
Lee DuHyeong
Publication year - 2020
Publication title -
journal of prosthodontics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.902
H-Index - 60
eISSN - 1532-849X
pISSN - 1059-941X
DOI - 10.1111/jopr.13171
Subject(s) - fiducial marker , image registration , matching (statistics) , artificial intelligence , computer vision , radiography , computed tomography , computer science , nuclear medicine , mathematics , medicine , image (mathematics) , radiology , statistics
Purpose Image registration of the optical intraoral scan to computed tomography image is essential for computer‐guided implant surgery. The remaining teeth, which are considered to be congruent structures observed in the scan and radiographic images, are used to perform the image registration. The purpose of this study was to evaluate the effects of the distribution of matching fiducial points on the accuracy of the image registration. Materials and Methods A partially edentulous model with three anterior remaining teeth was prepared. Two mini dental implants were inserted in the posterior edentulous areas on both sides, and computed tomography and surface scan data were obtained. Three groups were set according to the distribution of the image matching points used: localized distribution, unilateral distribution, and bilateral distribution. Fifteen graduate students performed the registration process in each group using the same image matching method. The accuracy of image registration was evaluated by measuring the geometric discrepancies between the radiographic and registered scan images in the anterior, middle, and posterior regions. One‐way and two‐way analysis of variance with the Tukey HSD post hoc test were used for statistical analysis (α = 0.05) Results In general, the registration discrepancy was lowest in the bilateral distribution group, followed by the unilateral distribution and localized distribution groups ( p < 0.001). In the regional analysis, the registration error tended to increase as the measurement region moved farther from the matching points. The distribution of the matching points and measurement regions had a statistical interaction in the accuracy of image registration. Conclusion The accuracy of image registration of the surface scan to the computed tomography is affected by the matching point distribution that can be improved by placing artificial markers in the edentulous areas.