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Application of V-detector in dental diagnosis

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).

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Application of V-detector in dental diagnosis

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

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

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

  4. Lateral view skull X-ray

  5. Existing diagnosis method • Angle’s classification: angle ANB (3 in the picture) N A B

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

  7. Remove artificial parts

  8. Binarization using multiple thresholds

  9. Choose thresholds & decide reference point • T0 = Vmax, • T1 = Vmax − (Vmax − Vmin)/nT , • ..., • TnT−1 = Vmax − (nT − 1)(Vmax − Vmin)/nT , Binarized at the highest threshold

  10. Extract four featuresat 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

  11. Experiment results

  12. Compare with SVM

  13. Using half of normal data to train

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

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