Thresholding of Histopathological Images of Oral Mucosa for Identification of Precancerous Oral Submucous Fibrosis (OSF) Cells: A Novel Entropy based Approach

摘要

The problem of early detection of Oral Submucous fibrosis (OSF) has received paramount importance in recent times. OSF is a chronic, irreversible and high risk pre-cancerous state of the oral mucosa. This kind of inflammatory and progressive fibrosis of the submucosal tissues is linked to oral cancers. This state results from chewing of areca nut which is prevalent in large parts of the Indian subcontinent. The current work presents an approach for the analysis of dysplastic epithelial cells from OSF, based on nuclear-cytoplasmic (N:C) ratio which is one of the most important morphological features to distinguish between normal and dysplastic epithelial cells. The proposed approach uses MATLAB to analyse the OSF biopsy images. This may help pathologists in identification of pre-cancer affected cells and in prevention and treatment of oral cancer. The methodology presented here can also be used for identification of epithelial atypia, an important light microscopic criteria that differentiates between normal and pre-malignant/malignant status of the oral mucosa.