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Impact of Matching Point Selections on Image Registration Accuracy between Optical Scan and Computed Tomography

The point-based surface registration method involves the manual selection process of paired matching points on the data of computed tomography and optical scan. The purpose of this study was to investigate the impact of selection error and distribution of fiducial points on the accuracy of image mat...

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Detalles Bibliográficos
Autores principales: Mai, Hai Yen, Lee, Du-Hyeong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426779/
https://www.ncbi.nlm.nih.gov/pubmed/32802841
http://dx.doi.org/10.1155/2020/3285431
Descripción
Sumario:The point-based surface registration method involves the manual selection process of paired matching points on the data of computed tomography and optical scan. The purpose of this study was to investigate the impact of selection error and distribution of fiducial points on the accuracy of image matching between 3-dimensional (3D) images in dental planning software programs. Computed tomography and optical scan images of a partial edentulous dental arch were obtained. Image registration of the optical scan image to computed tomography was performed using the point-based surface registration method in planning software programs under different conditions of 3 fiducial points: point selection error (0, 1, or 2 mm), point distribution (unilateral, bilateral), and planning software (Implant Studio, Blue Bio Plan) (n = 5 per condition, N = 60). The accuracy of image registration at each condition was evaluated by measuring linear discrepancies between matched images at X, Y, and Z axes. Kruskal-Wallis test, Mann-Whitney U test with Bonferroni correction, and 3-way analysis of variance were used to statistically analyse the measurement data (α = 0.05). No statistically significant difference was exhibited between the 0 and 1 mm point mismatch conditions in either unilateral or bilateral point distributions. The discrepancy values in the 2 mm mismatch condition were significantly different from the other mismatch conditions, especially in the unilateral point distribution (P < 0.05). Strong interactions among point selection error, distribution, and software programs on the image registration were found (P < 0.001). Minor matching point selection error did not influence the accuracy of point-based automatic image registration in the software programs. When the fiducial points are distributed unilaterally with large point selection error, the image matching accuracy could be decreased.