Abstract
Lungs pneumonia is one of the most dangerous diseases that affect the human lung. Pneumonia is often caused by bacteria, or viruses, fungi .and It affects one or all parts of the lung The X-ray image is one of the most diagnoses tools that used in medical field to detect pneumonia. Therefore, in this paper, deep learning method as wavelet scattering network implemented as classification model of lung pneumonia. Besides, the X-Ray images features extraction have been implemented by wavelet scattering transform. Since wavelet scattering networks need high replication datasets for training and testing wavelet scattering model, 500 X-Ray images for pneumonia and 500 Normal X-ray have been used to training data and the creation of reliable training details automatic identification images. In this work, networks will gain information from pre-trained networks on 650 images datasets, and 350 images are used for testing. The proposed system results specify that the wavelet scattering network classified chest X-ray images by accuracy reached to 98 %.
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