High-Fidelity 3D Imaging of Dental Scenes Using Gaussian Splatting.

Journal: Journal of dental research
Published Date:

Abstract

Three-dimensional visualization is increasingly used in dentistry for diagnostics, education, and treatment design. The accurate replication of geometry and color is crucial for these applications. Image-based rendering, which uses 2-dimensional photos to generate photo-realistic 3-dimensional representations, provides an affordable and practical option, aiding both regular and remote health care. This study explores an advanced novel view synthesis (NVS) method called Gaussian splatting (GS), a differentiable image-based rendering approach, to assess its feasibility for dental scene capturing. The rendering quality and resource usage were compared with representative NVS methods. In addition, the linear measurement trueness of extracted craniofacial meshes was evaluated against a commercial facial scanner and 3 smartphone facial scanning apps, while teeth meshes were assessed against 2 intraoral scanners and a desktop scanner. GS-based representation demonstrated superior rendering quality, achieving the highest visual quality, fastest rendering speed, and lowest resource usage. The craniofacial measurements showed similar trueness to commercial facial scanners. The dental measurements had larger deviations than intraoral and desktop scanners did, although all deviations remained within clinically acceptable limits. The GS-based representation shows great potential for developing a convenient and cost-effective method of capturing dental scenes, offering a balance between color fidelity and trueness suitable for clinical applications.

Authors

  • C-X Jin
    Department of Prosthodontics, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School and Hospital of Stomatolog, Wuhan University, China.
  • M-X Li
    Department of Prosthodontics, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School and Hospital of Stomatolog, Wuhan University, China.
  • H Yu
    School of Forensic Medicine, China Medical University, Shenyang 110001, China.
  • Y Gao
    Institute of Organ Transplantation, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Key Laboratory of Ministry of Health, Key Laboratory of Ministry of Education, Wuhan, China.
  • Y-P Guo
    Department of Prosthodontics, State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School and Hospital of Stomatolog, Wuhan University, China.
  • G-S Xia
    School of Artificial Intelligence, Wuhan University, China.
  • C Huang
    4 Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.