Conference proceeding
3D human airway segmentation for virtual bronchoscopy
Proceedings of SPIE, Vol.4683(1), pp.16-29
Medical Imaging 2002: Physiology and Function from Multidimensional Images
04/22/2002
DOI: 10.1117/12.463580
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.
Details
- Title: Subtitle
- 3D human airway segmentation for virtual bronchoscopy
- Creators
- Atilla P Kiraly - The Pennsylvania State Univ. (USA)William E Higgins - The Pennsylvania State Univ. and Univ. of Iowa College of Medicine (USA)Eric A Hoffman - Univ. of Iowa College of Medicine (USA)Geoffrey McLennan - Univ. of Iowa College of Medicine (USA)Joseph M Reinhardt - Univ. of Iowa (USA)
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.4683(1), pp.16-29
- Conference
- Medical Imaging 2002: Physiology and Function from Multidimensional Images
- DOI
- 10.1117/12.463580
- ISSN
- 0277-786X
- Language
- English
- Date published
- 04/22/2002
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Internal Medicine; Radiology
- Record Identifier
- 9984051874702771
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