Oral Cancer Detection: Feature Extraction & SVM Classification

Oral or mouth neoplasm is the type of head & neck cancers. This type of cancer starts in the throat or mouth due to uncontrollable growth of tissues, and it looks like a lump or bump. In the pre- processing step, anisotropic diffusion filter used to filter unwanted distortions from MRI image. Next, the lesion separated from MRI image using a hybrid approach KFCM clustering in segmentation and features extracted using Intensity of Histogram, GLCM & GLRLM. The comparison between these three algorithms is performed to obtain the best feature extraction technique. Next, SVM classifier used to classify the lesion. Classification accuracy obtained for the developed system is 98.04% using GLRLM feature extraction technique.