Our study investigates the accuracy and duration needed for 3D model registration using artifical intelligence (AI) assistance compared to conventional point-based registration. Manual segmentation of all cone beam computed tomography (CBCT) scans will be performed before the registration procedure.
CBCT images and intraoral scans will be screened following specific eligibility criteria. 16 CBCT images and intraoral scans that will meet the inclusion criteria will undergo manual segmentation via 3D medical image processing software. Afterward, point-based registration and AI-assisted registration will be performed by a single operator using specialized implant planning software. Then, the registration accuracy will be examined by measuring the distances between the three-dimensional models of CBCT data and intraoral scans. Also, the duration required for registration will be calibrated and recorded by a stopwatch.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
OTHER
Masking
NONE
Enrollment
16
We will use artificial intelligence to register 3d model on intra-oral scan
We will use five references points or more to perform model registration
Private maxillofacial digital lab
Cairo, Egypt
Registration accuracy
Distance between registered 3d model and CBCT in millimeters
Time frame: immediately after the procedure
Duration for registration
time taken for registration procedure
Time frame: During the procedure
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