AI advances orthodontics

AI-assisted growth prediction advances orthodontics

October 16, 2025
8:48 pm

Orthodontic treatment is most effective when timed to coincide with a child's growth peak. Traditionally, clinicians estimate growth by examining X-ray images of the cervical vertebrae—the neck bones visible in routine dental radiographs. However, this process requires careful manual annotation of specific points on the bones, a task that is both time-consuming and prone to variation between observers.

In Medical Image Analysis, researchers from Korea University Anam Hospital, KAIST, and the University of Ulsan introduce an artificial intelligence (AI) system designed to overcome these challenges.

The work, led by Dr. Jinhee Kim and Professor In-Seok Song, presents the Attend-and-Refine Network (ARNet-v2), an interactive deep learning model that streamlines growth assessment from a single lateral cephalometric radiograph.

ARNet-v2 automatically identifies skeletal landmarks on cervical vertebrae, allowing clinicians to predict a child’s pubertal growth peak. Unlike conventional techniques, the model requires minimal input: a single manual correction can be propagated across related anatomical points in the image, significantly improving both efficiency and accuracy.

AI-assisted growth prediction advances orthodontics

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