3D human airway segmentation for virtual bronchoscopy

A. P. Kiraly, W. E. Higgins, W. E. Higgins, E. A. Hoffman, G. McLennan, Joe M. Reinhardt

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


This paper describes a new airway segmentation algorithm that improves the speed of morphological-based segmentation approaches. Airway segmentation methods based on morphological operators suffer from the indiscriminant application of all operators to a large area. Using the results of three-dimensional (3D) region growing, the discrete application of larger operators is possible. This change can greatly decrease the execution time of the algorithm. This hybrid approach typically runs 5 to 10 times faster than the original algorithm. 3D adaptive region growing, morphological segmentation, and the hybrid approach are then compared via data obtained from human volunteers using a Marconi MX8000 scanner with the lungs held at 85% TLC. Results show that filtering improves robustness of these techniques. The hybrid approach allows for the practical use of morphological operators to create a clinically useful segmentation. We also demonstrate the method's utility for peripheral nodule analysis in a human case.

Original languageEnglish (US)
Pages (from-to)16-29
Number of pages14
JournalProceedings of SPIE-The International Society for Optical Engineering
StatePublished - 2002

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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