ArticleInternational journal of computer assisted radiology and surgery2024
Computer-assisted preoperative planning system with an automated registration method in prosthesis-driven oral implantology.
Article in International journal of computer assisted radiology and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeDentition 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.
methodsBased 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.
resultsVerification 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.
conclusionsThe 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.
Indexed as
Identifiers
37979039What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.