automatic approach for lung segmentation with juxta-pleural nodules from thoracic ct based on contour tracing and correction
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ID: 189622
2016
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Abstract
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±69.63 cm3, volume overlap error (VOE) 3.5057±1.3719%, average surface distance (ASD) 0.7917±0.2741 mm, root mean square distance (RMSD) 1.6957±0.6568 mm, maximum symmetric absolute surface distance (MSD) 21.3430±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.
| Reference Key |
wang2016computationalautomatic
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|---|---|
| Authors | ;Jinke Wang;Haoyan Guo |
| Journal | advanced functional materials |
| Year | 2016 |
| DOI |
10.1155/2016/2962047
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