Helicobacter Pylori Classification based on Deep Neural Network

Abstract

In this paper, a helicobacter pylori classification method based on deep neural network (Inception v3) was proposed. The purpose of the proposed model is to provide physicians with reference to the diagnosis of Helicobacter pylori infection for increasing the diagnostic efficiency. Data augmentation and transfer learning are exploited for model construction to generate a classification system with high prediction accuracy. To evaluate the performance of the proposed method, many endoscope images are collected for testing. Experimental results show that the proposed method can well determine whether the input image contains Helicobacter pylori or not.