Detection of Necrosis in Mice Liver Tissue Using Deep Convolutional Neural Network

Acute Hepatic Necrosis is an early sign of liver dysfunction. Liver dysfunction is one of the major reasons for increasing death rate. Accurate diagnosis in less time, along with proper medication, show a ray of hope in controlling the aggravation of the situation. To overcome the unfavorable effects of harmful drugs, medicinal plant extract has become major thrust area nowadays. This research work has presented a way to show the improvements in mice liver tissue after applying the designated composition of the plant extract. And the performance is measured with our designed deep convolutional neural network (CNN) architecture along with the preprocessing techniques that has shown to be competent to classify microscopic images of mice hepatic tissues. Considering a small database of 30 images, we introduced a preprocessing stage which included the dividing of the original microscopic images to small patches. The accuracy of the classification results using the proposed CNN based classifier was 99.33%.