title: The prediction in computer color matching of dentistry based on GA+BP neural network.
abstract: Although the use of computer color matching can reduce the influence of subjective factors by technicians, matching the color of a natural tooth with a ceramic restoration is still one of the most challenging topics in esthetic prosthodontics. Back propagation neural network (BPNN) has already been introduced into the computer color matching in dentistry, but it has disadvantages such as unstable and low accuracy. In our study, we adopt genetic algorithm (GA) to optimize the initial weights and threshold values in BPNN for improving the matching precision. To our knowledge, we firstly combine the BPNN with GA in computer color matching in dentistry. Extensive experiments demonstrate that the proposed method improves the precision and prediction robustness of the color matching in restorative dentistry.
authors: School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China.
authors: Haisheng
authors: H
authors: Li
authors: School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China.
authors: Long
authors: L
authors: Lai
authors: Peking University School and Hospital of Stomatology, Beijing 100081, China.
authors: Li
authors: L
authors: Chen
authors: Peking University School and Hospital of Stomatology, Beijing 100081, China.
authors: Cheng
authors: C
authors: Lu
authors: School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China.
authors: Qiang
authors: Q
authors: Cai
mesh_terms: D000465:Algorithms; D003764:Dental Materials; D003813:Dentistry / Q000379:methods*; D006801:Humans; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D017797:Prosthesis Coloring / Q000379:methods*; D011476:Prosthodontics / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software
chemical_list: D003764:Dental Materials