An automated airway segmentation algorithm for CT images using topological leakage detection and volume freezing

Syed Ahmed Nadeem; Eric A Hoffman; Punam K Saha

doi:10.1109/ICPR.2018.8545491

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Conference proceeding

An automated airway segmentation algorithm for CT images using topological leakage detection and volume freezing

Syed Ahmed Nadeem, Eric A Hoffman and Punam K Saha

2018 24th International Conference on Pattern Recognition (ICPR), Vol.2018-, pp.1181-1186

08/2018

DOI: 10.1109/ICPR.2018.8545491

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Abstract

Numerous multi-center studies related to chronic obstructive pulmonary disease use computed tomography (CT) based characterization of the lung parenchyma and bronchial tree to understand the disease's status and progression. To our knowledge, there are no fully automated methods for airway tree segmentation that don't require post-segmentation manual revision and intervention. In this paper, we present a novel CT-based airway tree segmentation algorithm using topological leakage detection and volume freezing. The method is fully automated requiring no manual inputs or post-segmentation editing. It uses intensity-based connectivity and novel approaches of leakage detection and volume freezing to iteratively grow an airway tree starting from an initial seed inside the trachea. It begins with a conservative threshold and then, iteratively shifts toward generous threshold values. The method was applied on chest CT scans of ten non-smoking healthy subjects at total lung capacity, and the results were highly promising with no visual segmentation leakages.

Airway tree

Computed tomography

digital topology and geometry

Diseases

Feature extraction

Image segmentation

Junctions

leakage detection

segmentation

Skeleton

skeletonization

tree analysis

Urban areas

volume freezing

Details

Title: Subtitle: An automated airway segmentation algorithm for CT images using topological leakage detection and volume freezing
Creators: Syed Ahmed Nadeem - University of Iowa
Eric A Hoffman - University of Iowa
Punam K Saha - University of Iowa
Resource Type: Conference proceeding
Publication Details: 2018 24th International Conference on Pattern Recognition (ICPR), Vol.2018-, pp.1181-1186
Publisher: IEEE
DOI: 10.1109/ICPR.2018.8545491
ISSN: 1051-4651
Language: English
Date published: 08/2018
Academic Unit: Electrical and Computer Engineering; Roy J. Carver Department of Biomedical Engineering; Internal Medicine; Radiology
Record Identifier: 9984197428802771

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