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Barrett's esophagus is a diseased condition with abnormal changes of the cells in the esophagus. Intestinal metaplasia (IM) and gastric metaplasia (GM) are two sub-classes of Barrett's esophagus. As IM can progress to the esophageal cancer, the neoplasia (NPL), developing methods for classifying between IM and GM are important issues in clinical practice. We adopted a deep learning (DL) algorithm to classify three conditions of IM, GM, and NPL based on endimicroscopy images. We constructed a convolutional neural network (CNN) architecture to distinguish among three classes. A total of 262 endomicroscopy imaging data of Barrett's esophagus were obtained from the international symposium on biomedical imaging (ISBI) 2016 challenge. 155 IM, 26 GM and 55 NPL cases were used to train the architecture. We implemented image distortion to augment the sample size of the training data. We tested our …