The prediction in computer color matching of dentistry based on GA+BP neural network.

Journal: Computational and mathematical methods in medicine
PMID: 25873990

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

  • Haisheng Li
    School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China.
  • Long Lai
    School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China.
  • Li Chen
    Department of Endocrinology and Metabolism, Qilu Hospital, Shandong University, Jinan, China.
  • Cheng Lu
    Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, People's Republic of China. lv_cheng0816@163.com.
  • Qiang Cai
    School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China.

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