Fully automated system for three-dimensional bronchial morphology analysis using volumetric multidetector computed tomography of the chest

Raman Venkatraman, Raghav Raman, Bhargav Raman, Richard B. Moss, Geoffrey D. Rubin, Lawrence H. Mathers, Terry E. Robinson

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Recent advancements in computed tomography (CT) have enabled quantitative assessment of severity and progression of large airway damage in chronic pulmonary disease. The advent of fast multidetector computed tomography scanning has allowed the acquisition of rapid, low-dose 3D volumetric pulmonary scans that depict the bronchial tree in great detail. Volumetric CT allows quantitative indices of bronchial airway morphology to be calculated, including airway diameters, wall thicknesses, wall area, airway segment lengths, airway taper indices, and airway branching patterns. However, the complexity and size of the bronchial tree render manual measurement methods impractical and inaccurate. We have developed an integrated software package utilizing a new measurement algorithm termed mirror-image Gaussian fit that enables the user to perform automated bronchial segmentation, measurement, and database archiving of the bronchial morphology in high resolution and volumetric CT scans and also allows 3D localization, visualization, and registration.

Original languageEnglish (US)
Pages (from-to)132-139
Number of pages8
JournalJournal of Digital Imaging
Volume19
Issue number2
DOIs
StatePublished - Jun 2006
Externally publishedYes

Keywords

  • Automated measurement
  • Automation algorithm
  • Bronchial morphology
  • Computed tomography

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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