Validation of a novel <scp>AI</scp>‐based automated multimodal image registration of <scp>CBCT</scp> and intraoral scan aiding presurgical implant planning
The novel AI-driven method provided an accurate, time-efficient, and consistent multimodal IOS-CBCT registration, encompassing both soft and hard tissues. This approach stands as a valuable alternative to manual and semi-automated registration approaches in the presurgical implant planning workflow.
Authors
- Rocharles Cavalcante Fontenele (ORCID: https://orcid.org/0000-0002-6426-9768)
- Sohaib Shujaat (ORCID: https://orcid.org/0000-0002-6250-2650)
- Saleem Ali (ORCID: https://orcid.org/0009-0002-5239-7268)
- Bahaaeldeen M. Elgarba (ORCID: https://orcid.org/0000-0003-4936-6567)
- Reinhilde Jacobs (ORCID: https://orcid.org/0000-0002-3461-0363)
- Abdullah Swaity
- Jan Meeus (ORCID: https://orcid.org/0000-0002-0280-5123)
Institutions
- King Saud bin Abdulaziz University for Health Sciences (SA)
- Tanta University (EG)
- King Hussein Medical Center (JO)
- Karolinska Institutet (SE)
- King Abdullah International Medical Research Center (SA)
- National Guard Health Affairs (SA)
- KU Leuven (BE)
Publication Details
- Journal
- Clinical Oral Implants Research
- Published
- 2024-08-05
- DOI
- https://doi.org/10.1111/clr.14338
- Citations
- 22
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 10.86