Conference proceeding
Topological leakage detection and freeze-and-grow propagation for improved CT-based airway segmentation
Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol.10574, pp.105741A-105741A-11
03/02/2018
DOI: 10.1117/12.2293309
Abstract
Numerous large multi-center studies are incorporating the use of computed tomography (CT)-based characterization of the lung parenchyma and bronchial tree to understand chronic obstructive pulmonary disease status and progression. To the best of our knowledge, there are no fully automated airway tree segmentation methods, free of the need for user review. A failure in even a fraction of segmentation results necessitates manual revision of all segmentation masks which is laborious considering the thousands of image data sets evaluated in large studies. In this paper, we present a novel CT-based airway tree segmentation algorithm using topological leakage detection and freeze-and-grow propagation. The method is fully automated requiring no manual inputs or post-segmentation editing. It uses simple intensity-based connectivity and a freeze-and-grow propagation algorithm to iteratively grow the airway tree starting from an initial seed inside the trachea. It begins with a conservative parameter and then, gradually shifts toward more generous parameter values. The method was applied on chest CT scans of fifteen subjects at total lung capacity. Airway segmentation results were qualitatively assessed and performed comparably to established airway segmentation method with no major visual leakages.
Details
- Title: Subtitle
- Topological leakage detection and freeze-and-grow propagation for improved CT-based airway segmentation
- Creators
- Syed Ahmed Nadeem - University of IowaEric A Hoffman - University of IowaJered P Sieren - Vida DiagnosticsPunam K Saha - University of Iowa
- Contributors
- Elsa D Angelini (Editor) - Imperial College LondonBennett A Landman (Editor) - Vanderbilt University
- Resource Type
- Conference proceeding
- Publication Details
- Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol.10574, pp.105741A-105741A-11
- Publisher
- SPIE
- DOI
- 10.1117/12.2293309
- ISSN
- 1605-7422
- Language
- English
- Date published
- 03/02/2018
- Academic Unit
- Electrical and Computer Engineering; Roy J. Carver Department of Biomedical Engineering; Internal Medicine; Radiology
- Record Identifier
- 9984197234202771
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