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X-ray radiography in animals has the difficulty of interpretation due to a variety of animals. This leads to image misinterpretation for a non-specialist veterinarian in some clinics that has no radiologist. Based on statistics of veterinary specialists in the US in 2018, the role of radiologist currently faces a shortage problem, especially in the fields of veterinary, which has only 4.2% from all of the other veterinarians. In this paper, we proposed an animal X-ray diagnosis application, namely Pet-X, focusing on the lung lesion problem which has difficulty in interpreting and need to be inspected in many respiratory and cardiovascular related cases. Pet-X automatically learns the sets of dogs and cats thoracic radiograph images, consisting of two positions which are in lateral and ventrodorsal position, pre-processes the images and generates the lung lesion diagnosis model using deep learning techniques (i.e., Convolutional …