A deep learning approach for dental implant planning in cone-beam computed tomography images
Abstract Background The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images. Methods Seventy-five CBCT images were included in this study. In these images, bone height and thi...
Main Authors: | Sevda Kurt Bayrakdar, Kaan Orhan, Ibrahim Sevki Bayrakdar, Elif Bilgir, Matvey Ezhov, Maxim Gusarev, Eugene Shumilov |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2021-05-01
|
Series: | BMC Medical Imaging |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12880-021-00618-z |
Similar Items
-
Comparison of the different voxel sizes in the estimation of peri-implant fenestration defects using cone beam computed tomography: an ex vivo study
by: Mehmet Hakan Kurt, et al.
Published: (2020-10-01) -
Interpretasi cone beam computed tomography 3-dimension dalam pemasangan implan dental di RumahSakit Gigi MulutFakultas Kedokteran Gigi Universitas Padjajaran (Interpretation of cone beam computed tomography 3-dimension in inserting dental implant at Dental Hospital of Faculty of Dentistry Padjajaran University)
by: Farina Pramanik, et al.
Published: (2015-02-01) -
Space analysis of the maxillary anterior bone geometry to understand anatomical limitation: and implant simulation study using cone-beam computed tomography (CBCT)
by: Lee, Wongi
Published: (2016) -
Retrospective study of the success of dental implants placed in HIV positive patients at the Henry M. Goldman School of Dental Medicine
by: Cordero, Nadine
Published: (2018) -
Positional Accuracy of Prosthetic Treatment Plan Incorporation Into Cone-beam Computed Tomography Scans Using Surface Scan Superimposition
by: Jamjoom, Faris Zainalabedeen
Published: (2017)