Textural pattern classification for oral squamous cell carcinoma.
J Microsc
; 269(1): 85-93, 2018 01.
Article
em En
| MEDLINE
| ID: mdl-28768053
ABSTRACT
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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Neoplasias Bucais
/
Carcinoma de Células Escamosas
/
Microscopia
Limite:
Humans
Idioma:
En
Revista:
J Microsc
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Índia