Objectives To determine whether AI systems that recognize cephalometric landmarks can
apply to various patient groups and to examine the patient‐related factors associated with …

Objectives To compare detection patterns of 80 cephalometric landmarks identified by an
automated identification system (AI) based on a recently proposed deep-learning method …

INTRODUCTION: Our objective was to compare the reliability of landmark identification with
hard-copied film images vs monitor-displayed images from digital lateral cephalograms …

Objective: The purpose of the present study was to evaluate reliability of a system that
performs automatic recognition of anatomic landmarks and adjacent structures on lateral …

Background To evaluate the techniques used for the automatic digitization of cephalograms
using artificial intelligence algorithms, highlighting the strengths and weaknesses of each …

Materials and methods Digital image processing algorithms (edge-based and
morphological) in addition to mathematical algorithms (knowledge-based) were used to …

Objective To compare the accuracy of cephalometric landmark identification between
artificial intelligence (AI) deep learning convolutional neural networks (CNN) You Only Look …

Computerized cephalometric analysis can include both landmark identification and
determination of linear or angular measurements. Although its use is time saving compared …

Objectives The purpose of this study was to design software for localization of cephalometric
landmarks and to evaluate its accuracy in finding landmarks. Methods 40 digital …

Objective: To describe the techniques used for automatic landmarking of cephalograms,
highlighting the strengths and weaknesses of each one and reviewing the percentage of …