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The locations of lung nodules relative to the other lung anatomical structures are important hints of malignant cancers. In this paper, we propose a fully automatic method to identify if a lung nodule is well-circumscribed, juxta-vascular, juxta-pleural or pleural tail in computed tomography (CT) images. First, we design an optimized graph model, introducing new global and region-based energy terms, to label each voxel as background or foreground in a single graph cut algorithm. Then, the texture features of a lung nodule are extracted based on the voxel labeling outputs, and its location information is inferred. We evaluate the proposed method on low-dose CT images, and demonstrate highly effective nodule classification results comparatively.