Segmentation-Guided Hybrid Deep Learning for Pulmonary Nodule Detection and Risk Prediction from Multi-Cohort CT Images

The results demonstrate that hybrid segmentation-guided CNN-Transformer architectures can effectively improve both diagnostic accuracy and clinical reliability in lung cancer screening. By combining precise nodule localization with calibrated malignancy risk estimation, the proposed framework offers a promising tool for supporting radiologists in LDCT-based lung cancer assessment.