DETECTION OF LIVER DISEASE BASED ON FULLY CONVOLUTIONAL NEURAL NETWORK AND DEEP LEARNING

DETECTION OF LIVER DISEASE BASED ON FULLY CONVOLUTIONAL NEURAL NETWORK AND DEEP LEARNING

            Nathiya Devi K1, Shaik Sohail 2, Walazapet Chandramanoj3, Sorakayalapalem Naveen Kumar4

     1Electronics And Communication Engineering, R.M.D. Engineering College

     2Electronics And Communication Engineering, R.M.D. Engineering College

     3Electronics And Communication Engineering, R.M.D. Engineering College

     4Electronics And Communication Engineering, R.M.D. Engineering College

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Abstract – Liver disease is one of the most dreadful diseases. It is difficult to identify in the present situation. In our proposed work, the fully convolutional neural network (FCNN) has been initiated for liver disease to recognize and sort out the current issue. Here computed tomography (CT) images taken and distinguish the CT scans as healthy and unhealthy. Our proposed work includes extraction of images as input. By using CNN algorithm, the model will be trained and classify based on the labeled training set. The concept of deep learning shows the decision making of the pre-trained data of neural network through the inner layers of images which leads to predictions.

 Key Words:  Fully Convolutional Neural Network, Computed Tomography, Convolutional neural network