Premium
Textural pattern classification for oral squamous cell carcinoma
Author(s) -
RAHMAN T.Y.,
MAHANTA L.B.,
CHAKRABORTY C.,
DAS A.K.,
SARMA J.D.
Publication year - 2018
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12611
Subject(s) - oral submucous fibrosis , basal cell , medicine , biopsy , pathological , cancer , abnormality , pathology , radiology , psychiatry
Summary Despite being an area of cancer with highest worldwide incidence, oral cancer yet remains to be widely researched. Studies on computer‐aided analysis of pathological slides of oral cancer contribute a lot to the diagnosis and treatment of the disease. Some researches in this direction have been carried out on oral submucous fibrosis. In this work an approach for analysing abnormality based on textural features present in squamous cell carcinoma histological slides have been considered. Histogram and grey‐level co‐occurrence matrix approaches for extraction of textural features from biopsy images with normal and malignant cells are used here. Further, we have used linear support vector machine classifier for automated diagnosis of the oral cancer, which gives 100% accuracy.