3D distribution of dental plaque on occlusal surface using 2D-fluorescence-image to 3D-surface registration

被引:10
作者
Chen, Qingguang [1 ]
Jin, Xing [1 ]
Zhu, Haihua [2 ]
Salehi, Hassan S. [3 ]
Wei, Kaihua [1 ]
机构
[1] Hangzhou Dianzi Univ, Sch Automat, Hangzhou 310018, Peoples R China
[2] Zhejiang Univ, Affiliated Hosp Stomatol, Hangzhou 310018, Peoples R China
[3] Calif State Univ Chico, Dept Elect & Comp Engn, Chico, CA 95929 USA
基金
中国国家自然科学基金;
关键词
3D distribution; Image processing; Algorithms; Dental plaque; Occlusal surface; 2D-3D registration; ICP; ENAMEL SURFACE; CARIES; MORPHOLOGY; FLUORESCENCE; BIOFILM;
D O I
10.1016/j.compbiomed.2020.103860
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The accumulation of dental plaque on a tooth surface plays a crucial role in developing dental caries. In this paper, fluorescence imaging modality with structured light-based intraoral 3D scanner were combined to investigate the 3D distribution of dental plaque. The traditional fluorescence imaging method only reveals the 2D spatial distribution of the dental plaque on a tooth surface. To visualize the 3D distribution of the dental plaque on an occlusal surface, mapping a 2D fluorescence image to a 3D occlusal surface was investigated. An iterative closest point (ICP)-based contour registration method was proposed. A fluorescence camera was calibrated to obtain intrinsic parameters. The rotation and translation matrices for projecting the 3D occlusal surface were optimized to match the contours of the 2D fluorescence image and the 3D projected model. The 3D distribution of occlusal plaque reveals that dental plaque accumulation relates to the local and global morphology of the tooth surface. Thus, the depth of the pit-and-fissure is not the only parameter used to determine plaque content. The investigation of the 3D distribution of occlusal plaque using 2D-3D registration paves the path for the quantitative analysis of the tooth surface morphology to perform plaque-guided caries risk assessment.
引用
收藏
页数:9
相关论文
共 37 条
  • [1] EARLY PLAQUE ACCUMULATION - A SIGN FOR CARIES RISK IN YOUNG-CHILDREN
    ALALUUSUA, S
    MALMIVIRTA, R
    [J]. COMMUNITY DENTISTRY AND ORAL EPIDEMIOLOGY, 1994, 22 (05) : 273 - 276
  • [2] Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque
    Angelino, Keith
    Shah, Pratik
    Edlund, David A.
    Mohit, Mrinal
    Yauney, Gregory
    [J]. BMC ORAL HEALTH, 2017, 17
  • [3] Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis
    Chen, Q. G.
    Zhu, H. H.
    Xu, Y.
    Lin, B.
    Chen, H.
    [J]. LASER PHYSICS, 2015, 25 (08)
  • [4] Classification of pit and fissure for caries risk based on 3D surface morphology analysis of tooth
    Chen, Qingguang
    Jin, Xing
    Zhu, Haihua
    Salehi, Hassan S.
    [J]. LASERS IN DENTISTRY XXVI, 2020, 11217
  • [5] Discrimination of Dental Caries Using Colorimetric Characteristics of Fluorescence Spectrum
    Chen, Qingguang
    Zhu, Haihua
    Xu, Ying
    Lin, Bin
    Chen, Hui
    [J]. CARIES RESEARCH, 2015, 49 (04) : 401 - 407
  • [6] Generation of 3D digital models of the dental arches using optical scanning techniques
    Claus, D.
    Radeke, J.
    Zint, M.
    Vogel, A. B.
    Satravaha, Y.
    Kilic, F.
    Hibst, R.
    Lapatki, B. G.
    [J]. SEMINARS IN ORTHODONTICS, 2018, 24 (04) : 416 - 429
  • [7] Approximal morphology as predictor of approximal caries in primary molar teeth
    Cortes, A.
    Martignon, S.
    Qvist, V.
    Ekstrand, Kim Rud
    [J]. CLINICAL ORAL INVESTIGATIONS, 2018, 22 (02) : 951 - 959
  • [8] Coulthwaite L, 2009, BRIT DENT J, V207, DOI 10.1038/sj.bdj.2009.854
  • [9] de Paiva M.A.A., 2017, DENT ANATOMICAL FEAT
  • [10] Domejean S., 2016, J Contemp Dent Pract, V17, P774