title: Automatic Approach for Lung Segmentation with Juxta-Pleural Nodules from Thoracic CT Based on Contour Tracing and Correction.
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.
authors.affiliation: Department of Software Engineering, Harbin University of Science and Technology, Rongcheng, China.
authors.forename: Jinke
authors.identifier: 0000-0002-1755-4734
authors.initials: J
authors.lastname: Wang
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China.
authors.forename: Haoyan
authors.identifier: 0000-0002-4951-2002
authors.initials: H
authors.lastname: Guo
mesh_terms: D000465:Algorithms; D001331:Automation; D016000:Cluster Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional; D008168:Lung / Q000000981:diagnostic imaging* / Q000503:physiopathology; D008171:Lung Diseases / Q000000981:diagnostic imaging*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D025341:Principal Component Analysis; D011857:Radiographic Image Interpretation, Computer-Assisted; D013902:Radiography, Thoracic; D015203:Reproducibility of Results; D012867:Skin / Q000473:pathology; D014057:Tomography, X-Ray Computed