Automatic approach for lung segmentation with juxta-pleural nodules from thoracic CT based on contour tracing and correction (Q2011752)

Summary: This paper presents a fully automatic framework for lung segmentation, in which juxta-pleural nodule problem is brought into strong focus. The proposed scheme consists of three phases: skin boundary detection, rough segmentation of lung contour, and pulmonary parenchyma refinement. Firstly, chest skin boundary is extracted through image aligning, morphology operation, and connective region analysis. Secondly, diagonal-based border tracing is implemented for lung contour segmentation, with maximum cost path algorithm used for separating the left and right lungs. Finally, by arc-based border smoothing and concave-based border correction, the refined pulmonary parenchyma is obtained. The proposed scheme is evaluated on 45 volumes of chest scans, with volume difference (VD) \(11.15 \pm 69.63\)\,cm, volume overlap error (VOE) \(3.5057 \pm 1.3719\)\%, average surface distance (ASD) \(0.7917 \pm 0.2741\)\,mm, root mean square distance (RMSD) \(1.6957 \pm 0.6568\)\,mm, maximum symmetric absolute surface distance (MSD) \(21.3430 \pm 8.1743\)\,mm, and average time-cost 2 seconds per image. The preliminary results on accuracy and complexity prove that our scheme is a promising tool for lung segmentation with juxta-pleural nodules.