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Automatic approach for lung segmentation with juxta-pleural nodules from thoracic CT based on contour tracing and correction. (English) Zbl 1423.92184
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.
##### MSC:
 92C55 Biomedical imaging and signal processing
##### Keywords:
lung segmentation; thoracic CT; contour tracing; correction
VTK; MITK
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