Publication Detail Page

A. Kiraly, W. E. Higgins, E. A. Hoffman, G. McLennan, and J. M. Reinhardt. 3D human airway segmentation for virtual bronchoscopy. In A. V. Clough and C.-T. Chen, eds., Proc. SPIE Conf. Medical Imaging, vol. 4683, pp. 16-29, San Diego, CA, 2002.

Abstract: 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.

Citation: BibTeX format    Endnote format

Keywords: airways bronchoscopy

Other publications by: A. Kiraly, W. E. Higgins, E. A. Hoffman, G. McLennan, J. M. Reinhardt

Related journal papers:
Related conference papers:
Related theses:
The Reinhardt Biomedical Imaging Lab