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Updated: Jul 10, 2025
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
Published on: August 5, 2021
Computer-assisted preoperative planning system with an automated registration method in prosthesis-driven oral
Yueang Liu1, Mingjun Gong1, Baoxin Tao2
1School of Mechanical Engineering, Shanghai Jiao Tong University, Room 925, Dongchuan Road 800, Minhang District, Shanghai, China.
Purpose:
Dentition defect including edentulism is a problem that deserves attention, which requires precise preoperative planning. The trajectories of the implants can be determined using a pre-made radiographic template, which is adopted for prosthesis-driven oral implantology. However, existing solutions for the registration between the radiographic template and the patient's CBCT still require manual operation and cause inadequate accuracy. In this study, a pre-operative planning system for prosthesis-driven oral implantology is developed with a novel automated registration method.
Methods:
Based on threshold segmentation and morphological feature filtering, the potential feature points on two sets of CBCTs are, respectively, recognized. The distance features of the point sets are used to predict the optimal solution for point pair matching, after which the automated registration is implemented. The prosthesis-driven planning can be completed according to the results of registration and multi-planar reconstruction. Then, the surgical templates can be designed and fabricated using 3D printing technology based on the planning results and finally used for intra-operative guidance during implant placement.
Results:
Verification of the proposed method was conducted on three clinical cases. The mean Fiducial Registration Error of 0.13 ± 0.01mm was achieved with great efficiency. The average time was 0.15 s for the automatic registration algorithm, and 15.64 s for the whole procedure.
Conclusions:
The proposed method proved to be accurate and robust. The results indicate that it can achieve higher efficiency while maintaining a low error level, which will have great potential clinical applications in the future.
