Three-Dimensional Tooth Model Reconstruction Using Statistical Randomization-Based Particle Swarm Optimization

The registration between images is a crucial part of the 3-D tooth reconstruction model. In this paper, we introduce a registration method using our proposed statistical randomization-based particle swarm optimization (SR-PSO) algorithm with the iterative closet point (ICP) method to find the optima...

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Bibliographic Details
Main Authors: Ritipong Wongkhuenkaew, Sansanee Auephanwiriyakul, Marasri Chaiworawitkul, Nipon Theera-Umpon
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/5/2363
Description
Summary:The registration between images is a crucial part of the 3-D tooth reconstruction model. In this paper, we introduce a registration method using our proposed statistical randomization-based particle swarm optimization (SR-PSO) algorithm with the iterative closet point (ICP) method to find the optimal affine transform between images. The hierarchical registration is also utilized in this paper since there are several consecutive images involving in the registration. We implemented this algorithm in the scanned commercial regular-tooth and orthodontic-tooth models. The results demonstrated that the final 3-D images provided good visualization to human eyes with the mean-squared error of 7.37 micrometer<sup>2</sup> and 7.41 micrometer<sup>2</sup> for both models, respectively. From the results compared with the particle swarm optimization (PSO) algorithm with the ICP method, it can be seen that the results from the proposed algorithm are much better than those from the PSO algorithm with the ICP method.
ISSN:2076-3417