Abstract: Chest CT scan is the primary medical imaging method performed for the early screening and diagnosis of lung cancer. Deep-learning based computer aided diagnosis (CAD) system for chest CT imaging is helpful for detecting and classifying pulmonary nodules. Deep-learning techniques can improve the performance of CAD systems, especially in enhancing the accuracy of pulmonary nodule detection and reducing false-positive rates. This article reviewed the current application status of deep-learning models in CAD systems and the progress that has been achieved in using these systems for imaging pulmonary nodules.