关键词: 卷积神经网络, 胸片, 肺结节, 图像分类

Abstract: The characteristics of pulmonary nodules are complex, which make it difficult to detect lung nodules in chest radiographs. A classification method of lung nodules based on deep neural network is proposed. In this method, the difference between the brightness and the gray level of the chest is reduced by the consistency of the grayscale of the chest. Secondly, the characteristics of the lung nodules can be extracted by the different data amplification methods, and the lung nodules are identified by the improved neural network frame. The proposed algorithm effectively avoids the loss of the feature part of the image during the segmentation of the chest image, and overcomes the shortcomings of the lung nodule characterized by the complexity of the chest image. The results show that the average accuracy of the thoracic lung nodules is 84.2%. It has a certain application value in the classification and identification of pulmonary nodules in medical chest radiographs.

Key words: convolution neural network, chest radiographs, pulmonary nodules, image classification