Objective：To investigate the early imaging features of pulmonary nodules which are ≤ 10 mm in diameter by computed tomography（CT）. Methods：A total of 152 cases with pulmonary nodules which were pathologically confirmed from April 2014 to November 2020 were collected，including 51 benign cases and 101 malignant cases. Imaging features including average diameter，density（solid，mixed ground glass，purely ground glass），position，relationship between lesions and pleura（subpleural，away from the pleura），shape（round，oval，irregular），boundary（clear，unclear），margin（lobulation，spiculation sign），air-bronchogram sign，vacuole sign，vessel convergence sign，central vessel signs，pleural indentation sign，satellite foci and alteration of the adjacent bronchioles were assessed. The sensitivity，specificity，accuracy，the positive predictive value and negative predictive value were calculated by comparison of the results analyzed by Shenrui Pulmonary Nodule Analysis Software and the gold standard to determine valuable imag－ing features. Results：According to the analysis of the software，among the 152 cases，there were 94 malignant cases（62 cases of lung adenocarcinoma，30 cases of carcinoma in situ，1 case of carcinoid and 1 case of squamous cell carcinoma），47 benign cases（5 cases of tumor-like hyperplasia，3 cases of hamartoma，34 cases of inflammatory granuloma，3 cases of inflammatory pseudotumor，1 case of fungal infection and 1 case of fibrous carbon nodule）. The results of the lung nodule analysis software demonstrated the sensitivity，specificity，accuracy，the positive predic－tive value and negative predictive value were 93.06%，92.15%，92.76%，95.91% and 87.03% respectively，which were consistent with the pathological results after surgery. Conclusion：CT-imaging analysis based on AI pulmonary nodule analysis software has a great differential value in qualitative diagnosis of pulmonary nodules ≤ 10 mm in diameter.