  Fundamental to improving Dental and Orthodontic treatments is the ability to
quantitatively assess and cross-compare their outcomes. Such assessments
require calculating distances and angles from 3D coordinates of dental
landmarks. The costly and repetitive task of hand-labelling dental models
impedes studies requiring large sample size to penetrate statistical noise. We
have developed techniques and software implementing these techniques to map out
automatically, 3D dental scans. This process is divided into consecutive steps
- determining a model's orientation, separating and identifying the individual
tooth and finding landmarks on each tooth - described in this paper. Examples
to demonstrate techniques and the software and discussions on remaining issues
are provided as well. The software is originally designed to automate Modified
Huddard Bodemham (MHB) landmarking for assessing cleft lip/palate patients.
Currently only MHB landmarks are supported, but is extendable to any
predetermined landmarks. This software, coupled with intra-oral scanning
innovation, should supersede the arduous and error prone plaster model and
caliper approach to Dental research and provide a stepping-stone towards
automation of routine clinical assessments such as "index of orthodontic
treatment need" (IOTN).
