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Pulmonary nodule is the early manifestation of lung cancer. For the detection and classification of benign and malignant lung nodules, an improved LVQ classifier algorithm is proposed. Firstly, the C-V algorithm is used to do the lung parenchyma segmentation on the original images. Then, the optimal threshold method is used to extract the region of interest. Multiple clustering algorithms are used to detect pulmonary nodules after feature extraction and feature normalization. The classification of benign and malignant pulmonary nodules is carried out by an improved LVQ classifier. The experimental results prove that the improved algorithm has a higher rate of diagnosis on the classification of benign and malignant pulmonary nodules.