Three-dimensional human airway segmentation methods for clinical virtual bronchoscopy.

Abstract:

RATIONALE AND OBJECTIVES:The segmentation of airways from CT images is a critical first step for numerous virtual bronchoscopic (VB) applications. Automatic or semiautomatic methods are necessary, since manual segmentation is prohibitively time consuming. The methods must be robust and operate within a reasonable time frame to be useful for clinical VB use. The authors developed an integrated airway segmentation system and demonstrated its effectiveness on a series of human images. MATERIALS AND METHODS:The authors' airway segmentation system draws on two segmentation algorithms: (a) an adaptive region-growing algorithm and (b) a new hybrid algorithm that uses both region growing and mathematical morphology. Images from an ongoing VB study were segmented by means of both the adaptive region-growing and the new hybrid methods. The segmentation volume, branch number estimate, and segmentation quality were determined for each case. RESULTS:The results demonstrate the need for an integrated segmentation system, since no single method is superior for all clinically relevant cases. The region-growing algorithm is the fastest and provides acceptable segmentations for most VB applications, but the hybrid method provides superior airway edge localization, making it better suited for quantitative applications. In addition, the authors show that prefiltering the image data before airway segmentation increases the robustness of both region-growing and hybrid methods. CONCLUSION:The combination of these two algorithms with the prefiltering options allowed the successful segmentation of all test images. The times required for all segmentations were acceptable, and the results were suitable for the authors' VB application needs.

journal_name

Acad Radiol

journal_title

Academic radiology

authors

Kiraly AP,Higgins WE,McLennan G,Hoffman EA,Reinhardt JM

doi

10.1016/s1076-6332(03)80517-2

keywords:

subject

Has Abstract

pub_date

2002-10-01 00:00:00

pages

1153-68

issue

10

eissn

1076-6332

issn

1878-4046

journal_volume

9

pub_type

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