Automated lung segmentation in X-ray computed tomography: development and evaluation of a heuristic threshold-based scheme.
OBJECTIVE
To develop and evaluate a reliable, fully-automated lung segmentation scheme for application in X-ray computed tomography.


METHODS
The automated scheme was heuristically developed using a slice-based, pixel-value threshold and two sets of classification rules. Features used in the rules include size, circularity, and location. The segmentation scheme operates slice-by-slice and performs three key operations: (1) image preprocessing to remove background pixels, (2) computation and application of a pixel-value threshold to identify lung tissue, and (3) refinement of the initial segmented regions to prune incorrectly detected airways and separate fused right and left lungs.


RESULTS
The performance of the automated segmentation scheme was evaluated using 101 computed tomography cases (91 thick slice, 10 thin slice scans). The 91 thick cases were pre- and post-surgery from 50 patients and were not independent. The automated scheme successfully segmented 94.0% of the 2,969 thick slice images and 97.6% of the 1,161 thin slice images. The mean difference of the total lung volumes calculated by the automated scheme and functional residual capacity plus 60% inspiratory capacity was -24.7 +/- 508.1 mL. The mean differences of the total lung volumes calculated by the automated scheme and an established, commonly used semi-automated scheme were 95.2 +/- 52.5 mL and -27.7 +/- 66.9 mL for the thick and thin slice cases, respectively.


CONCLUSIONS
This simple, fully-automated lung segmentation scheme provides an objective tool to facilitate lung segmentation from computed tomography scans.
Leader
Joseph K
JK
Department of Radiology, University of Pittsburgh, Imaging Research Division, 300 Halket St, Suite 4200, Pittsburgh, PA 15213, USA.
Zheng
Bin
B
Rogers
Robert M
RM
Sciurba
Frank C
FC
Perez
Andrew
A
Chapman
Brian E
BE
Patel
Sanjay
S
Fuhrman
Carl R
CR
Gur
David
D
D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging*; D008171:Lung Diseases / Q000000981:diagnostic imaging; D011656:Pulmonary Emphysema / Q000000981:diagnostic imaging; D012985:Software Design; D014057:Tomography, X-Ray Computed / Q000379:methods*