Using Novel Method with Convolutional Neural Network for Colorectal Cancer Classification

Abstract

Detection of diseases with the help of computer has helped the doctors in recognizing the colorectal cancer more efficiently,that further helps in treatment and increases the survival rate of patients.This paper shows our work on  classification of endoscopic images using convolutional neural network(CNN). The proposed network preserves the spatial details of endoscopic images by changing the dilation factor. It is said that if the dimensionality of an image is reduced, the image may loss spatial details, which may result in confusion among similar looking polyps or may even miss detection of polyps. In our model we also use regularization technique to overcome the problems like noise, artifacts and overfitting. For evaluating over models we have used matrices namely accuracy matrix, precision matrix, recall matrix and F1-score. Our model gives higher accuracy when compared with traditional models for classification of endoscopic images.