Classification of leukoplakia using svm

Precancerous lesions such as leukoplakia possess a high risk of transformation into oral cancer. This can be prevented if they are diagnosed and treated in the earlier stages. Besides various available pathological investigations and molecular research works , attempts are also being made by computer analysts to find out a technique that could accurately diagnose and classify these diseases. One such attempt has been made in this research work by using SVM (Support Vector Machine) to classify leukoplakia lesions from normal oral mucosa. BICC (Block Intensity Code Comparison) features were extracted from microscopic images of leukoplakia -affected mucosae and used for the aboveesaid classification. The performance was evaluated based on the sensitivity, specificity and accuracy of the results.