Automatic classification method and system for frosted pulmonary nodules

The invention discloses an automatic classification method and system for frosted pulmonary nodules, and the method mainly comprises the following steps: processing and analyzing a chest CT image through an image processing method, feature engineering and a machine learning technology, effectively distinguishing frosted pulmonary nodules representing lung micro-invasive adenocarcinoma and invasiveadenocarcinoma, and carrying out the quantitative evaluation of a classification effect. The method effectively fuses various image features of pulmonary nodules reflecting iconographic characterization, can realize automatic classification of frosted pulmonary nodules characterizing lung micro-invasive adenocarcinoma and invasive adenocarcinoma, provides auxiliary information for doctors, helpsdoctors to perform quantitative analysis, and improves the working efficiency. In addition, clinical guidance significance can be provided for feasibility of the frosted pulmonary nodule classification method through a numeric