Fully Automated Segmentation of Lung Parenchyma Using Break and Repair Strategy

The traditional segmentation methods available for pulmonary parenchyma are not accurate because most of the methods exclude nodules or tumors adhering to the lung pleural wall as fat. In this paper, several techniques are exhaustively used in different phases, including two-dimensional (2D) optimal...

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Bibliographic Details
Published in:Journal of intelligent systems 2019-04, Vol.28 (2), p.275-289
Main Authors: Kumar, S. Pramod, Latte, Mrityunjaya V.
Format: Article
Language:English
Subjects:
62H35
68T99
68U10
Amputation
Automation
Bresenham method
Carcinogens
Computed tomography
improved chain code
Lungs
Methods
Nodules
pulmonary parenchyma
Segmentation
Sodium
Temperature
thoracic CT slice
Tumors
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Summary:The traditional segmentation methods available for pulmonary parenchyma are not accurate because most of the methods exclude nodules or tumors adhering to the lung pleural wall as fat. In this paper, several techniques are exhaustively used in different phases, including two-dimensional (2D) optimal threshold selection and 2D reconstruction for lung parenchyma segmentation. Then, lung parenchyma boundaries are repaired using improved chain code and Bresenham pixel interconnection. The proposed method of segmentation and repairing is fully automated. Here, 21 thoracic computer tomography slices having juxtapleural nodules and 115 lung parenchyma scans are used to verify the robustness and accuracy of the proposed method. Results are compared with the most cited active contour methods. Empirical results show that the proposed fully automated method for segmenting lung parenchyma is more accurate. The proposed method is 100% sensitive to the inclusion of nodules/tumors adhering to the lung pleural wall, the juxtapleural nodule segmentation is >98%, and the lung parenchyma segmentation accuracy is >96%.
ISSN:0334-1860
2191-026X
DOI:10.1515/jisys-2017-0020