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Proceedings Paper

3D human airway segmentation for virtual bronchoscopy
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Paper 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.

Paper Details

Date Published: 24 April 2002
PDF: 14 pages
Proc. SPIE 4683, Medical Imaging 2002: Physiology and Function from Multidimensional Images, (24 April 2002); doi: 10.1117/12.463580
Show Author Affiliations
Atilla Peter Kiraly, The Pennsylvania State Univ. (United States)
William E. Higgins, The Pennsylvania State Univ. and Univ. of Iowa College of Medicine (United States)
Eric A. Hoffman, Univ. of Iowa College of Medicine (United States)
Geoffrey McLennan, Univ. of Iowa College of Medicine (United States)
Joseph M. Reinhardt, Univ. of Iowa (United States)


Published in SPIE Proceedings Vol. 4683:
Medical Imaging 2002: Physiology and Function from Multidimensional Images
Anne V. Clough; Chin-Tu Chen, Editor(s)

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