Notice: Users may be experiencing issues with displaying some pages on stanfordhealthcare.org. We are working closely with our technical teams to resolve the issue as quickly as possible. Thank you for your patience.
 

Learn about the flu shot, COVID-19 vaccine, and our masking policy »

Stanford Health Care

Fully automated system for three-dimensional bronchial morphology analysis using volumetric multidetector computed tomography of the chest JOURNAL OF DIGITAL IMAGING Venkatraman, R., Raman, R., Raman, B., Moss, R. B., Rubin, G. D., Mathers, L. H., Robinson, T. E. 2006; 19 (2): 132-139

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.

View details for DOI 10.1007/s10278-005-9240-0

View details for Web of Science ID 000238317500007

View details for PubMedID 16341571

View details for PubMedCentralID PMC3045191