Application of V-detector in dental diagnosis To be submitted to CEC 2006

background Malocclusion – diagnosis using X-ray V-detector – one-class classification

malocclusion Different types: I (normal bite), II (overbite), and III (underbite) Mild or severe (functional)

Lateral view skull X-ray

Existing diagnosis method Angles classification: angle ANB (3 in the picture) N A B

Feature extraction Brightness distribution instead of entity identification Binarization at multiple threshold Quantitatize each binary image with four real numbers

Remove artificial parts

Binarization using multiple thresholds

Choose thresholds & decide reference point T0 = Vmax, T1 = Vmax (Vmax Vmin)/n T,..., T nT1 = Vmax (n T 1)(Vmax Vmin)/n T, Binarized at the highest threshold

Extract four features at each threshold (a) Horizontal displacement x = xwhite x0, (b) Vertical displacement y = ywhite y0, (c) Displacement distance r = mean of distances between white pixels to (x0, y0) (d) Area mass A = total number of white pixel/width · height

Experiment results

Compare with SVM

Using half of normal data to train

summary A novel feature extraction is proposed. V-detector shows some potentials. Issue: a lot more normal data are desired.