Initial estimation of landmark location for automated cephalometric analysis using template matching method

An initial estimator algorithm, aims to localize the position of anatomical landmarks in lateral cephalogram, is presented. This proposed algorithm explores the use of affine transform and template matching to detect three essential reference points: two cephalostat projections (ear rods and nasal-positioner) and menton. The detection of cephalostat projections using template matching method are conducted in the first step. The second step, in which the initial menton positions and small expectation windows for menton are computed, is implemented using affine transform. The exact position of menton is then located within the expectation window using template matching method with sum of squared differences-based similarity measurement in the final step. Using a ten-fold cross validation scheme, we test the algorithm on 106 direct-digital lateral cephalograms. The experimental results show that the initial estimator can efficiently limit the search areas. The obtained detection rate within 4 mm accuracy window is 92.5 percent.