AN EFFICIENT ALGORITHMIC SOLUTION FOR AUTOMATIC SEGMENTATION OF LUNGS FROM CT IMAGES

A novel technique for lung segmentation from input Computed Tomography (CT) images using optimal thresholding was developed. Initially, the CT image was segmented by optimal thresholding. The lung volume was obtained using connected component labeling method by removing irrelevant information. The r...

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Bibliographic Details
Published in:Pakistan journal of science Vol. 70; no. 1; pp. 71 - 78
Main Authors: Shaukat, F, Raja, G
Format: Journal Article
Language:English
Published: Lahore Knowledge Bylanes 31.03.2018
Pakistan Association for the Advancement of Science
Subjects:
Algorithms
Automation
CAT scans
Computed tomography
Consortia
Image databases
Image processing
Image segmentation
Industrialized nations
Labeling
Lung cancer
Lungs
Medical imaging
Methods
Morphology
Tomography
United States > US
East Asia
ISSN:0030-9877, 2411-0930
Online Access:Get full text
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Summary:A novel technique for lung segmentation from input Computed Tomography (CT) images using optimal thresholding was developed. Initially, the CT image was segmented by optimal thresholding. The lung volume was obtained using connected component labeling method by removing irrelevant information. The resultant image contained holes which were filled by morphological operations. A novel technique to separate the lungs was introduced which effectively separated the right and left lungs. Finally, the lung contour was smoothed by rolling ball algorithm to include any juxta pleural nodules. The proposed system was evaluated using 84 scans of publicly available dataset Lung Image Database Consortium (LIDC). The proposed system achieved an overlap measure of 0.985 and the root mean square difference between the proposed method and ground truth was 0.47 mm.  
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ISSN:0030-9877
2411-0930
DOI:10.57041/vol70iss1pp71-78