Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm.

@article{Krishnan2012AutomatedOC,
  title={Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm.},
  author={Nisha Devi Muthu Krishnan and Vikram Venkatraghavan and U. Rajendra Acharya and Mousumi Pal and Ranjan Rashmi Paul and Lim Choo Min and Ajoy Kumar Ray and Jyotirmoy Chatterjee and Chandan Chakraborty},
  journal={Micron},
  year={2012},
  volume={43 2-3},
  pages={
          352-64
        }
}
Oral cancer (OC) is the sixth most common cancer in the world. In India it is the most common malignant neoplasm. Histopathological images have widely been used in the differential diagnosis of normal, oral precancerous (oral sub-mucous fibrosis (OSF)) and cancer lesions. However, this technique is limited by subjective interpretations and less accurate diagnosis. The objective of this work is to improve the classification accuracy based on textural features in the development of a computer… CONTINUE READING
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