Automatic placement of simulated dental implants within CBCT images in optimum positions: a deep learning model

• Published in: Medical & biological engineering & computing Vol. 63; no. 8; pp. 2325 - 2339
• Main Authors: Alotaibi, Shahd, Alsomali, Mona, Alghamdi, Shatha, Alfadda, Sara, Alturaiki, Isra, Al-Ekrish, Asma’a, Altwaijry, Najwa
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2025; Springer Nature B.V
• Subjects: Accuracy; Artificial intelligence; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Bone density; Classification; Computed tomography; Computer Applications; Cone-Beam Computed Tomography - methods; Datasets; Deep Learning; Dental Implantation - methods; Dental Implants; Dental prosthetics; Dentistry; Dentists; Human Physiology; Humans; Imaging; Imaging, Three-Dimensional - methods; Jaw; Medical diagnosis; Medical research; Neural networks; Original Article; Planning; Radiology; Software; Teeth; Three dimensional imaging; Tomography; Deep learning; Regression; Computer vision; Classification; CBCT; Image detection

Implant dentistry is the standard of care for the replacement of missing teeth. It is a complex process where cone-beam computed tomography (CBCT) images are analyzed by the dentist to determine the implants’ length, diameter, and position, and angulation diameter, position, and angulation taking in...