Classification of Pathological Images Using Convolution Neural Networks

  • Rajashekhargouda C. Patil


Cancer can now be counted in the deceases with high mortality rate. Oral cancer is the cancer originating or affecting the oral cavity. Oral cavity consists of the inner part of the open mouth which is visible. Gold standard available for the detection of the oral cancer is through analysis of the microscopic obtained from the Hemotoxilin and Eosin (H&E) staining of the tissue biopsy images. In this paper trying to automate the classification of the above mentioned images with the help of Convolution Neural Networks and Support Vector Machines. The collection used for training the CNN for the feature extraction consists of 300 cancerous images and 60 normal images. Through the proposed approach we achieved the Sensitivity of 80 percent and the specificity of 60 percent.

Keywords: Oral Cancer, Pathological images, Convolutional Neural Network


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How to Cite
Patil, R. C. (2018). Classification of Pathological Images Using Convolution Neural Networks. Asian Journal For Convergence In Technology (Founded by ISB &M School of Technology )), 4(I). journals.v4iI.461
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