A Review on Automatic Cephalometric Landmark Identification Using Artificial Intelligence Techniques

Abstract

Accurate identification of landmarks from lateral cephalograms plays an important role in cephalometric analysis. Cephalometrics helps orthodontists, dentists, and maxillofacial surgeons to figure out the anatomical abnormalities and thereby provides optimal treatment planning. As the manual marking procedures are measurement error prone and consumes time, a grand challenge is organized by IEEE to automate the detection of landmarks from cephalometric radiographs in the International Symposium on Biomedical Imaging (ISBI) 2014 and 2015. This paper presents a review and comparison for various Artificial Intelligence Techniques proposed to automate cephalometric landmark identification from x-ray images.