Automated Cephalometric Landmarking Using Artificial Intelligence - A Systematic Review

Abstract

Background: Cephalometry is the field of studying the measurement of the dimensions of the head, contemporarily on X-ray images, is regularly used in fields such as orthodontics, dentofacial orthopedics and maxillofacial surgery to assess, predict and modulate growth, formulate a treatment plan, evaluate the effects of the treatment, and compare cases. Research in the area of automated cephalometric landmark detection and analysis with artificial intelligence has seen significant advances over the last 20 years

Methods: Research articles from the Pubmed, MEDLINE, and Google scholar databases within the last 20 years with keywords Artificial Intelligence, Neural networks, orthodontics, and Cephalometry were selected for this review.  11 articles were considered for the final qualitative analysis.

Results: There have been significant improvements in the field of automating the identification of cephalometric landmarks. There seems to be a developing interest in this field with a gradual increase in research of automated cephalometry. The advantages and limitations of A.I.-based solutions for the field of Orthodontics are unique thus demanding careful application of this technology.

Conclusion: The current state and potential of A.I.-driven systems in Orthodontic cephalometric landmarking and analysis requires careful understanding and deliberation to ensure meaningful progress in this field..