Objective. This paper uses the nearest neighbor propagation clustering segmentation algorithm to explore the impact of PET/CT image segmentation technology on lung cancer radiotherapy planning. Methods. In this paper, PET/CTscan was performed on 12 patients with nonmetastatic lung cancer. The self-written automatic segmentation program based on PCNN model is used to segment the PETtarget area, and then the tumor target area is manually sketched based on CTimages and PET/CTimages, and the intensity-modulated radiotherapy plan is formulated with the same parameters. Target volume and dose distribution were analyzed. Results. There was no statistical difference between the PET automatic segmentation target area and the PET manual contouring target area (P < 0.05); the segmentation method was accurate and reliable; the difference between the CT manual contouring target area was statistically significant (P0.05). Conclusion. Based on the nearest neighbor propagation clustering segmentation algorithm, PET/CT image segmentation technology improves the accuracy of tumor target area delineation. The radiotherapy plan based on the segmentation target area can reduce the normal tissue exposure range and reduce the incidence of complications.