Yonggan Nian

Abstract Early detection of pulmonary nodules plays a critical role in improving the survival rate of patients with lung cancer. However, existing detection methods often exhibit limited feature stability and inadequate contextual awareness, particularly when handling small nodules or nodules with complex structures. To address these limitations, we propose a 3D detection method, termed TCMNet. The proposed model consists of two key components.