Rapidly developing technologies are emerging every day in different fields, especially in a medical environment. However, still, some old techniques are quite popular, efficient and effective in this manner. X-rays are one of these techniques for detection of bone fractures. Nevertheless, sometimes the size of fractures is not significant and could not be detected easily. Therefore, effective and intelligent systems should be designed. This paper aims to develop an intelligent classification system that would be capable of detecting and classifying the bone fractures. The developed system comprises of two principal stages. In the first stage, the images of the fractures are processed using different image processing techniques in order to detect their location and shapes and the next stage is the classification phase, where a backpropagation neural network is trained and then tested on processed images. Experimentally, the system was tested on different bone fracture images and the results show high efficiency and a classification rate.
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