Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans. (arXiv:2109.11941v2 [cs.CV] UPDATED)

Accurately segmenting teeth and identifying the corresponding anatomical
landmarks on dental mesh models are essential in computer-aided orthodontic
treatment. Manually performing these two tasks is time-consuming, tedious, and,
more importantly, highly dependent on orthodontists' experiences due to the
abnormality and large-scale variance of patients' teeth. Some machine
learning-based methods have been designed and applied in the orthodontic field
to automatically segment dental meshes (e.g., intraoral scans). In contrast,
the number of studies on tooth landmark localization is still limited. This …

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