A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition.

AIM: To describe a novel neural network based oral precancer (oral submucous fibrosis; OSF) stage detection method.

METHOD: The wavelet coefficients of transmission electron microscopy images of collagen fibres from normal oral submucosa and OSF tissues were used to choose the feature vector which, in turn, was used to train the artificial neural network.

RESULTS: The trained network was able to classify normal and oral precancer stages (less advanced and advanced) after obtaining the image as an input.

CONCLUSIONS: The results obtained from this proposed technique were promising and suggest that with further optimisation this method could be used to detect and stage OSF, and could be adapted for other conditions.