Status
Conditions
Treatments
About
The Aim of the study is to evaluate Accuracy of automated mandibular defect reconstruction using Artificial intelligence and assessing impact on aesthetic and occlusion outcomes using patient-specific reconstruction plates.
Full description
The digital surgical process often requires an expected mandibular reference model. Currently, the common digital surgery process, is to mirror repair or manually look for other similar mandibles for local data fusion and smoothing processing. A more accurate expected reference model is difficult to achieve, time consuming and difficult to promote in clinical practice. Moreover, rapid routing processing often has poor accuracy. For cumulative bilateral lesions, massive lesions, obvious displacement or lesions cross the middle line, there is still no effective method to predict the expected reference model in clinical practice.
The main objective for conducting this study is to propose an improved algorithm to overcome the drawbacks of recent studies using 3D Unet and to test the predictability and clinical value of virtually generated 3d models of defected mandible in real patients.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Primary purpose
Allocation
Interventional model
Masking
4 participants in 1 patient group
Loading...
Central trial contact
Sarah Moustafa. Moustafa, MSc.; Sarah Moustafa. Moustafa, PHD
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal