Automated lung segmentation in X-ray computed tomography: development and evaluation of a heuristic threshold-based scheme

Acad Radiol. 2003 Nov;10(11):1224-36. doi: 10.1016/s1076-6332(03)00380-5.


Rationale and objectives: To develop and evaluate a reliable, fully-automated lung segmentation scheme for application in X-ray computed tomography.

Materials and 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.

Conclusion: This simple, fully-automated lung segmentation scheme provides an objective tool to facilitate lung segmentation from computed tomography scans.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Image Processing, Computer-Assisted
  • Lung / diagnostic imaging*
  • Lung Diseases / diagnostic imaging
  • Pulmonary Emphysema / diagnostic imaging
  • Software Design
  • Tomography, X-Ray Computed / methods*