The digital model for evaluating single edentulous area from CBCT images Computer-assisted implant surgery, CBCT, CNNs, AI
Conditions
Interventions
Region of interests that have been labelled by experts (a certified oral and maxillofacial
surgeon or a certified oral and maxillofacial radiologist).,Region of interests that have been labelled by CN
Diagnostic,Diagnostic
Experts,Model
Sponsors
Chulalongkorn University
Eligibility
Sex/Gender
All
Age
20 Years to No maximum
Inclusion criteria
Inclusion criteria: 1. The CBCT radiograph with at least 1 site of single missing tooth either inmaxilla or mandible 2. Present of mesial and distal adjacent teeth which at least 6 mm. of distance of crestal bone 3. Age at least 20 years old
Exclusion criteria
Exclusion criteria: 1. Radiographic sign with pathology in the jaw bone 2. Incomplete healing socket 3. Insufficient CBCT quality, such as excessive metal artifacts or movement artifacts 4. Adjacent teeth with indication for extraction, such as severe periodontal bone loss, extensive carious lesions 5. The edentulous ridge with no opposing teeth
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Accuracy The end of operation The types of errors made by a machine learning model,Time required for segmentation The end of operation Digital clock | — |
Secondary
| Measure | Time frame |
|---|---|
| Precision The end of operation The types of errors made by a machine learning model,Recall The end of operation The types of errors made by a machine learning model,F1 score The end of operation The types of errors made by a machine learning model,Different volume The end of operation Cubric mm.,Surface deviation The end of operation mm. | — |
Countries
Thailand
Contacts
Public ContactPattarapong Anupuntanun
Faculty of Dentistry , Chulalongkorn University
Outcome results
None listed