Classification of Leukoplakia Oral Disease using ANFIS Classifier

Abstract

 The discovery of oral spitefulness is an essential area of exploration in the literature now. About 82 of the cases are diagnosed at the early stage and 27 of the cases are diagnosed at the advanced stage. Beforehand discovery reduces the mortality rate of the cases. An automated approach is proposed to descry and member the oral cancer in oral Glamorous Resonance Images (MRI). The oral cancer regions are detected from the MR image using ANFIS classifier. The MR image is preprocessed for farther processing. From thatpre-processed image, the object discovery is performed. The coming processes are segmentation and point birth. The quality of the image is bettered using adaptive mean sludge and enhanced using adaptive histogram equalization fashion. The enhanced image is converted using Gabor transfigure and the features of the oral image are uprooted from this converted image. Eventually, these features are classified using ANFIS bracket approach. With the help of machine literacy fashion, the different cases of cells are also detected, discerned and spotted for the farther opinion. Morphological approaches are used to member the cancer region in the classified abnormal oral MRI images.