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This article describes the implementation of a model based on Deep Learning techniques applied to computational vision in the activity of classifying X-ray images as support in the diagnosis of traumatic lesions of the pelvic structure, specifically the acetabulum of the pelvis. In the area of Medical Sciences, nowadays, it is essential to have automated tools that support medical diagnosis. For the construction of these tools it is necessary to analyze the different techniques or methods provided by Computing, specifically Deep Learning, for the processing and interpretation of images and potentialize them with the application of GPUs to accelerate the achievement of results.