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Review
. 2022 Jun 16:2022:1880113.
doi: 10.1155/2022/1880113. eCollection 2022.

Cephalometric Analysis in Orthodontics Using Artificial Intelligence-A Comprehensive Review

Aravind Kumar Subramanian  1 , Yong Chen  1   2 , Abdullah Almalki  3 , Gautham Sivamurthy  4 , Dashrath Kafle  5
Affiliations
Review

Cephalometric Analysis in Orthodontics Using Artificial Intelligence-A Comprehensive Review

Aravind Kumar Subramanian et al. Biomed Res Int. .

Abstract

Artificial intelligence (AI) is a branch of science concerned with developing programs and computers that can gather data, reason about it, and then translate it into intelligent actions. AI is a broad area that includes reasoning, typical linguistic dispensation, machine learning, and planning. In the area of medicine and dentistry, machine learning is currently the most widely used AI application. This narrative review is aimed at giving an outline of cephalometric analysis in orthodontics using AI. Latest algorithms are developing rapidly, and computational resources are increasing, resulting in increased efficiency, accuracy, and reliability. Current techniques for completely automatic identification of cephalometric landmarks have considerably improved efficiency and growth prospects for their regular use. The primary considerations for effective orthodontic treatment are an accurate diagnosis, exceptional treatment planning, and good prognosis estimation. The main objective of the AI technique is to make dentists' work more precise and accurate. AI is increasingly being used in the area of orthodontic treatment. It has been evidenced to be a time-saving and reliable tool in many ways. AI is a promising tool for facilitating cephalometric tracing in routine clinical practice and analyzing large databases for research purposes.

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Conflict of interest statement

The authors declared there is no conflict of interest.

Figures

Figure 1
Figure 1
History of artificial intelligence.
Figure 2
Figure 2
Cephalometric tracing done using Dolphin Imaging technology.
Figure 3
Figure 3
Prediction of cephalometric landmarks using artificial intelligence.
Figure 4
Figure 4
Artificial intelligence approaches to identify landmarks.
See this image and copyright information in PMC

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