Xun Li1, Xin Wang2, Ming Chen3. 1. Shenzhen Graduate School, Harbin Institute of Technology (HIT), HIT Campus of University Town of Shenzhen, Shenzhen, China. Electronic address: lx_hit@163.com. 2. Shenzhen Graduate School, Harbin Institute of Technology (HIT), HIT Campus of University Town of Shenzhen, Shenzhen, China. Electronic address: wangxinsz@hit.edu.cn. 3. School of Computer Science and Information Engineering, Guangxi Normal University, 15 Yucai Road, Qixing District, Guilin, China. Electronic address: hustcm@hotmail.com.
Abstract
BACKGROUND: The accuracy of extraction of biological characteristic curves in tooth preparations directly determines whether the tooth restorations and preparations are closely matched to allow appropriate adhesion. Ultimately, these will affect the success of the dental restoration surgery. In the process to obtain the tooth preparation, the dentist is required to grind the tooth manually and fuzzy regions may thus exist. Multiple feature curves with locally increased curvatures exist in these fuzzy regions, but only the outermost is preferred. The characteristic curve consists of points, some with and some without extreme curvature values. This study aims to extract an accurate biological characteristic curve. METHOD: This challenging problem is mapped to the search of the minimum cost path for a graph, and is solved using the well-known A* algorithm. To identify the mapped graph, the outward direction coefficient is first introduced followed by the extremality coefficient node. Both of these coefficients ensure that the biological characteristic curve can be accurately extracted. RESULTS: The conducted experiment demonstrated that the proposed algorithm can rapidly, accurately, and automatically obtain the outermost feature curve which passes through the fuzzy region of the tooth preparation. Additionally, the part of the biological characteristic curve related to the non-fuzzy region can also be accurately extracted. CONCLUSIONS: The proposed algorithm significantly improves the accuracy of the extraction curve and the quality of the restoration design.
BACKGROUND: The accuracy of extraction of biological characteristic curves in tooth preparations directly determines whether the tooth restorations and preparations are closely matched to allow appropriate adhesion. Ultimately, these will affect the success of the dental restoration surgery. In the process to obtain the tooth preparation, the dentist is required to grind the tooth manually and fuzzy regions may thus exist. Multiple feature curves with locally increased curvatures exist in these fuzzy regions, but only the outermost is preferred. The characteristic curve consists of points, some with and some without extreme curvature values. This study aims to extract an accurate biological characteristic curve. METHOD: This challenging problem is mapped to the search of the minimum cost path for a graph, and is solved using the well-known A* algorithm. To identify the mapped graph, the outward direction coefficient is first introduced followed by the extremality coefficient node. Both of these coefficients ensure that the biological characteristic curve can be accurately extracted. RESULTS: The conducted experiment demonstrated that the proposed algorithm can rapidly, accurately, and automatically obtain the outermost feature curve which passes through the fuzzy region of the tooth preparation. Additionally, the part of the biological characteristic curve related to the non-fuzzy region can also be accurately extracted. CONCLUSIONS: The proposed algorithm significantly improves the accuracy of the extraction curve and the quality of the restoration design.