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Proceedings Paper

A simple method for automated lung segmentation in x-ray CT images
Author(s): Bin Zheng; J. Ken Leader; Glenn S. Maitz; Brian E. Chapman; Carl R. Fuhrman; Robert M. Rogers; Frank C. Sciurba; Andrew Perez; Paul Thompson; Walter F. Good; David Gur
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Paper Abstract

We developed and tested an automated scheme to segment lung areas depicted in CT images. The scheme includes a series of six steps. 1) Filtering and removing pixels outside the scanned anatomic structures. 2) Segmenting the potential lung areas using an adaptive threshold based on pixel value distribution in each CT slice. 3) Labeling all selected pixels ingo segmented regions and deleting isolated regions in non-lung area. 4) Labeling and filling interior cavities (e.g., pleural nodules, airway wall, and major blood vessels) inside lung areas. 5) Detecting and deleting the main airways (e.g., trachea and central bronchi) connected to the segmented lung areas. 6) Detecting and separating possible anterior or posterior junctions between the lungs. Five lung CT cases (7-10 mm in slice thickness) with variety of disease patterns were used to train or set up the classification rules in the scheme. Fifty examinations of emphysema patients were then used to test the scheme. The results were compared with the results generated from a semi-automated method with manual interaction by an expert observer. The experimental results showed that the average difference in estimated lung volumes between the automated scheme and manually corrected approach was 2.91%±0.88%. Visual examination of segmentation results indicated that the difference of the two methods was larger in the areas near the apices and the diaphragm. This preliminary study demonstrated that a simple multi-stage scheme had potential of eliminating the need for manual interaction during lunch segmentation. Hence, it can ultimately be integrated into computer schemes for quantitative analysis and diagnosis of lung diseases.

Paper Details

Date Published: 15 May 2003
PDF: 9 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.480290
Show Author Affiliations
Bin Zheng, Univ. of Pittsburgh (United States)
J. Ken Leader, Univ. of Pittsburgh (United States)
Glenn S. Maitz, Univ. of Pittsburgh (United States)
Brian E. Chapman, Univ. of Pittsburgh (United States)
Carl R. Fuhrman, Univ. of Pittsburgh (United States)
Robert M. Rogers, Univ. of Pittsburgh (United States)
Frank C. Sciurba, Univ. of Pittsburgh (United States)
Andrew Perez, Univ. of Pittsburgh (United States)
Paul Thompson, Univ. of Pittsburgh (United States)
Walter F. Good, Univ. of Pittsburgh (United States)
David Gur, Univ. of Pittsburgh (United States)


Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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