Early diagnosis of lung cancer plays a key role in improving the survival rate of pa-tients.The analysis of lung images by computer aided diagnostic system can help doctors to de-tect lesions early.In this paper,a deep learning framework combining ResNet and Transformer is proposed for the detection and classification of lung nodules in CT images,so as to realize the automatic diagnosis of early lung cancer.Firstly,data enhancement is carried out,and then ResNet's powerful feature extraction capability is utilized to obtain the deep features of the im-age.Meanwhile,Transformer is introduced to capture the long-range dependence relationship between features and enhance the models recognition ability of small changes in lung nodules.Experimental results show that the algorithm can effectively improve the accuracy and sensitivi-ty of early lung cancer detection.
关键词
肺癌早期诊断/计算机辅助诊断/ResNet/Transformer/深度学习
Key words
early diagnosis of lung cancer/Computer aided diagnosis/ResNet/Transformer/Deep learning
维普
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