scholarly journals Assessment of automatic cephalometric landmark identification using artificial intelligence

2021 ◽  
Author(s):  
Galina Bulatova ◽  
Budi Kusnoto ◽  
Viana Grace ◽  
T. Peter Tsay ◽  
David M. Avenetti ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Landmark Identification

scholarly journals Accuracy of Artificial Intelligence-Assisted Landmark Identification in Serial Lateral Cephalograms of Class III Patients Who Underwent Two-Jaw Orthognathic Surgery

2021 ◽  
Author(s):  
Mihee Hong ◽  
Inhwan Kim ◽  
Jin-Hyoung Cho ◽  
Kyung-Hwa Kang ◽  
Minji Kim ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Orthognathic Surgery ◽  
Class Iii ◽  
Test Set ◽  
Post Surgery ◽  
Landmark Identification ◽  
Lateral Cephalograms ◽  
Significant Difference ◽  
Before And After ◽  
Fixed Retainers

Abstract To compare the accuracy of artificial intelligence-assisted landmark identification in serial lateral cephalograms of Class III patients who underwent two-jaw orthognathic surgery using a convolutional neural network (CNN) algorithm. 3,188 lateral cephalograms of Class III patients were allocated into the training and validation sets (3,004 cephalograms of 751 patients) and test set (184 cephalograms of 46 patients; subdivided into the genioplasty and non-genioplasty groups, n=23 per group)]. Each patient in the test set had four cephalograms: initial (T0), pre-surgery [T1, presence of orthodontic brackets (OBs)], post-surgery [T2, presence of OBs and surgical plates and screws (S-PS)], and debonding [T3, presence of S-PS and fixed retainers (FR)]. Statistical analysis was performed using mean errors of 20 landmarks between human gold standard and the CNN model. The total mean error was 1.17 mm without significant difference among four time-points. Before and after surgery, ANS, A point, and B point showed an increased error, while Mx6D and Md6D showed a decreased error. No difference in errors existed at B point, Pogonion, Menton, Md1C, and Md1R between the genioplasty and non-genioplasty groups. The CNN model can be used for landmark identification in serial cephalograms despite presence of OB, S-PS, FR, genioplasty, and bone remodeling.

Artificial Intelligence

2009 ◽  
Author(s):  
David L. Poole ◽  
Alan K. Mackworth
Keyword(s):  
Artificial Intelligence

Review of Machines Who Think: A Personal Inquiry Into the History and Prospects of Artificial Intelligence.

1981 ◽  
Vol 26 (6) ◽  
pp. 484-484
Author(s):  
George Mandler
Keyword(s):  
Artificial Intelligence

The problems and promises of artificial intelligence

1979 ◽  
Author(s):  
Gregory Freiherr
Keyword(s):  
Artificial Intelligence
Sign in / Sign up

Export Citation Format

Share Document