Open AccessDetection and Segmentation of Cancer Regions in Oral MRI images using ANFIS Classification Method
Author(s) -
M.Praveena Kirubabai,
G Arumugam
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c5449.098319
Subject(s) - adaptive histogram equalization , artificial intelligence , histogram equalization , segmentation , gabor filter , pattern recognition (psychology) , stage (stratigraphy) , magnetic resonance imaging , computer science , image segmentation , cancer , median filter , computer vision , histogram , medicine , radiology , image processing , image (mathematics) , biology , paleontology
The detection of oral cancer is an important area of research in the literature today. About 82% of the patients are diagnosed at the early stage and 27% of the patients are diagnosed at the advanced stage. Early detection reduces the mortality rate of the patients. An automated approach is proposed to detect and segment the oral cancer in oral Magnetic Resonance Images (MRI). The quality of the image is improved using adaptive mean filter and enhanced using adaptive histogram equalization technique. The enhanced image is transformed using Gabor transform and the features of the oral image are extracted from this transformed image. These features are classified using ANFIS classification approach. Morphological approaches are used to segment the cancer region in the classified abnormal oral MRI images.