Automatic Approach for Lung Segmentation with Juxta-Pleural Nodules from Thoracic CT Based on Contour Tracing and Correction

作者：Wang, Jinke; Guo, Haoyan^*

来源：Computational and Mathematical Methods in Medicine, 2016, 2016: 2962047.

DOI：10.1155/2016/2962047

• COMPUTED-TOMOGRAPHY
• PULMONARY VESSELS
• INCLUSION
• IMAGES
• MODEL

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 cm(3), 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.

• 出版日期2016
• 单位哈尔滨工业大学; 哈尔滨学院