Airway Tree Segmentation in Serial Block-Face Cryomicrotome Images of Rat Lungs

Christian Bauer; Melissa A Krueger; Wayne J Lamm; Brian J Smith; Robb W Glenny; Reinhard R Beichel

doi:10.1109/TBME.2013.2277936

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Airway Tree Segmentation in Serial Block-Face Cryomicrotome Images of Rat Lungs

Journal article

Open access

Airway Tree Segmentation in Serial Block-Face Cryomicrotome Images of Rat Lungs

Christian Bauer, Melissa A Krueger, Wayne J Lamm, Brian J Smith, Robb W Glenny and Reinhard R Beichel

IEEE transactions on biomedical engineering, Vol.61(1), pp.119-130

01/2014

DOI: 10.1109/TBME.2013.2277936

PMCID: PMC3925465

PMID: 23955692

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Abstract

A highly automated method for the segmentation of airways in the serial block-face cryomicrotome images of rat lungs is presented. First, a point inside of the trachea is manually specified. Then, a set of candidate airway centerline points is automatically identified. By utilizing a novel path extraction method, a centerline path between the root of the airway tree and each point in the set of candidate centerline points is obtained. Local disturbances are robustly handled by a novel path extraction approach, which avoids the shortcut problem of standard minimum cost path algorithms. The union of all centerline paths is utilized to generate an initial airway tree structure, and a pruning algorithm is applied to automatically remove erroneous subtrees or branches. Finally, a surface segmentation method is used to obtain the airway lumen. The method was validated on five image volumes of Sprague-Dawley rats. Based on an expert-generated independent standard, an assessment of airway identification and lumen segmentation performance was conducted. The average of airway detection sensitivity was 87.4% with a 95% confidence interval (CI) of (84.9, 88.6)%. A plot of sensitivity as a function of airway radius is provided. The combined estimate of airway detection specificity was 100% with a 95% CI of (99.4, 100)%. The average number and diameter of terminal airway branches was 1179 and 159 μm, respectively. Segmentation results include airways up to 31 generations. The regression intercept and slope of airway radius measurements derived from final segmentations were estimated to be 7.22 μm and 1.005, respectively. The developed approach enables the quantitative studies of physiology and lung diseases in rats, requiring detailed geometric airway models.

Image segmentation

Airway segmentation

serial block-face imaging cryomicrotome

Lungs

rat lung

Biomedical measurement

Rats

Biomedical imaging

Details

Title: Subtitle: Airway Tree Segmentation in Serial Block-Face Cryomicrotome Images of Rat Lungs
Creators: Christian Bauer - Department of Electrical and Computer Engineering and the Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, USA
Melissa A Krueger - Department of Medicine, University of Washington, Seattle, WA, USA
Wayne J Lamm - Department of Medicine, University of Washington, Seattle, WA, USA
Brian J Smith - Department of Biostatistics, The University of Iowa, Iowa City, IA, USA
Robb W Glenny - Departments of Medicine and Physiology & Biophysics, University of Washington, Seattle, WA, USA
Reinhard R Beichel - Department of Electrical and Computer Engineering, the Department of Internal Medicine, and the Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, IA, USA
Resource Type: Journal article
Publication Details: IEEE transactions on biomedical engineering, Vol.61(1), pp.119-130
DOI: 10.1109/TBME.2013.2277936
PMID: 23955692
PMCID: PMC3925465
NLM abbreviation: IEEE Trans Biomed Eng
ISSN: 0018-9294
eISSN: 1558-2531
Publisher: IEEE
Language: English
Date published: 01/2014
Academic Unit: Electrical and Computer Engineering; Biostatistics; Holden Comprehensive Cancer Center
Record Identifier: 9983997474302771

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