Fully automated estimation of arch forms in cone-beam CT with cubic B-spline approximation: Evaluation of digital dental models with missing teeth

2021 ◽  
Vol 131 ◽  
pp. 104256
Author(s):  
Myungsoo Bae ◽  
Jae-Woo Park ◽  
Namkug Kim
Keyword(s):  
Cone Beam Ct ◽  
Spline Approximation ◽  
Cone Beam ◽  
Missing Teeth ◽  
B Spline ◽  
Dental Models ◽  
Digital Dental Models ◽  
Arch Forms

Semi-automatic and robust determination of dental arch form in dental cone-beam CT with B-spline approximation

2019 ◽  
Vol 172 ◽  
pp. 95-101 ◽  
Author(s):  
Myungsoo Bae ◽  
Jae-Woo Park ◽  
Namkug Kim
Keyword(s):  
Cone Beam Ct ◽  
Spline Approximation ◽  
Cone Beam ◽  
Dental Arch ◽  
Arch Form ◽  
B Spline ◽  
Dental Arch Form

Artifact-Resistant Superimposition of Digital Dental Models and Cone-Beam Computed Tomography Images

2013 ◽  
Vol 71 (11) ◽  
pp. 1933-1947 ◽  
Author(s):  
Hsiu-Hsia Lin ◽  
Wen-Chung Chiang ◽  
Lun-Jou Lo ◽  
Sam Sheng-Pin Hsu ◽  
Chien-Hsuan Wang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Cone Beam ◽  
Computed Tomography Images ◽  
Dental Models ◽  
Digital Dental Models

scholarly journals Comparison of linear and angular changes assessed in digital dental models and cone‐beam computed tomography

2019 ◽  
Vol 23 (1) ◽  
pp. 118-128 ◽  
Author(s):  
Camila Massaro ◽  
Carolina Losada ◽  
Lucia Cevidanes ◽  
Marilia Yatabe ◽  
Daniela Garib ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Cone Beam ◽  
Dental Models ◽  
Digital Dental Models

scholarly journals Evaluation of digital dental models obtained from dental cone-beam computed tomography scan of alginate impressions

2016 ◽  
Vol 46 (3) ◽  
pp. 129 ◽  
Author(s):  
Tingting Jiang ◽  
Sang-Mi Lee ◽  
Yanan Hou ◽  
Xin Chang ◽  
Hyeon-Shik Hwang
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Cone Beam ◽  
Computed Tomography Scan ◽  
Dental Models ◽  
Digital Dental Models ◽  
Tomography Scan

Dental Long Axes using Digital Dental Models Compared to Cone‐Beam Computed Tomography

2021 ◽  
Author(s):  
Amalia Cong ◽  
Camila Massaro ◽  
Antonio Carlos de Oliveira Ruellas ◽  
Mary Barkley ◽  
Marilia Yatabe ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Cone Beam ◽  
Dental Models ◽  
Digital Dental Models

scholarly journals An Algorithm for Automatically Extracting Dental Arch curve

2021 ◽  
Vol 2082 (1) ◽  
pp. 012018
Author(s):  
Shengshan Zhu ◽  
He Fang ◽  
Dawei Zhang
Keyword(s):  
Medical Diagnosis ◽  
Extraction Method ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
Dental Arch ◽  
Missing Teeth ◽  
Panoramic View ◽  
Fully Automatic ◽  
The One ◽  
Oral Condition

Abstract Dental cone beam CT (CBCT) scans, due to their low radiation dose, are now widely used in the medical diagnosis of patients’ oral cavity. The reconstruction of a panoramic view of the dental arch from the scanned CBCT data facilitates the dentist’s observation of the patient’s oral condition. The most important technique for reconstructing the dental arch panorama is the extraction of the dental arch curve accurately. The existing method is to rely on the experience of the dentist to manually connect the dental arch curve, or use techniques related to threshold segmentation to extract dental arch curve. These methods rely on the experience of dentists on the one hand. On the other hand, when there are interferences such as implants, metal tubes, braces or missing teeth in the patient’s mouth, the threshold calculation will be wrong. Based on this, this article starts with the histogram of CBCT data, and proposes a highly robust and fully automatic dental arch curve extraction method. In the actual experiment, the dental arch curves of 40 different patients were extracted, and all the dental arch curves can be accurately and automatically extracted, thus verifying the effectiveness of the proposed algorithm.

scholarly journals Virtual setup in orthodontics: planning and evaluation

2019 ◽  
Vol 24 (7) ◽  
pp. 2385-2393 ◽  
Author(s):  
F. Baan ◽  
O. de Waard ◽  
R. Bruggink ◽  
T. Xi ◽  
E. M. Ongkosuwito ◽  
...  
Keyword(s):  
Tooth Movement ◽  
Cone Beam Ct ◽  
Final Outcome ◽  
Inter Observer Variability ◽  
Dental Models ◽  
Digital Dental Models ◽  
Pre Treatment ◽  
Mean Differences ◽  
Iterative Closest Point Algorithm ◽  
High Level

Abstract Objectives The purpose of this study was to evaluate the clinical accuracy of virtual orthodontic setups by using a new CBCT-based approach. Materials and methods Ten patients who underwent pre-surgical orthodontics were included in this study. Pre-treatment and pre-surgical cone-beam CT (CBCT) scans and digital dental models were available. The pre-treatment digital dental model was used to create an orthodontic virtual setup. The digital dental models were fused with the corresponding CBCT scans, and the two CBCT scans were aligned using voxel-based matching. Moving each individual tooth from the virtual setup to the final outcome allows the calculation of the accuracy of the virtual setup by using an iterative closest point algorithm. Differences between virtual setup and final outcome were recorded as well as the ICC between two observers. Results The inter-observer variability showed a high level of agreement between the observers. The largest mean difference between observers was found in the cranial/caudal direction (0.36 ± 0.30 mm) and the roll rotation (1.54 ± 0.98°). Differences between the virtual setup and final outcome were small in the translational direction (0.45 ± 0.48 mm). Rotational mean differences were larger with the pitch of the incisors (0.00 ± 7.97°) and molars (0.01 ± 10.26°) as largest difference. Excessive extrusion of all upper teeth and more anterior movement than planned were seen for both upper and lower arch. Lower molars showed less extrusion. Clinical relevance The data of this study can be used to obtain more insight in the accuracy and achievability of orthodontic virtual setup. Tooth movement can now be studied in more details which can lead to new insights.

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