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Proceedings Paper

A probabilistic model for predicting diameters of lung airways
Author(s): Spencer Yuen; Matthew Brown; Sumit Shah; Hyun Jun Kim; Sarinnapha Vasunilashorn; Eric Kleerup; Jonathan Goldin M.D.
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Paper Abstract

The accurate characterization of pulmonary airways on CT is potentially very useful for diagnosis and evaluation of lung diseases. The task is challenging due to their small size and variable orientation. We propose a probabilistic modeling technique and a set of measurement tools to quantitate airway morphology. We extract the airway tree structure from high resolution CT scans with a seeded region growing algorithm. Individual airway branches are identified by reducing the airway tree to a set of central axes. Properties such as lumen diameter and branch angle are measured from these central axes. The structure of the Bayesian model is inferred from a set of equations representing the parent-daughter relationships between branches, such as equations of air flow ratio and flow conservation. The CT measurements are used to instantiate the conditional probability tables of the Bayesian model. To evaluate the model, it was used to predict the airway diameter for the 2nd, 3rd, 4th, 5th, and 6th generations of the airway tree. We show that the model can reasonably predict the diameter of a particular airway branch, given information of its parent.

Paper Details

Date Published: 29 April 2005
PDF: 11 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.595710
Show Author Affiliations
Spencer Yuen, Univ. of California/Los Angeles (United States)
Matthew Brown, Univ. of California/Los Angeles (United States)
Sumit Shah, Univ. of California/Los Angeles (United States)
Hyun Jun Kim, Univ. of California/Los Angeles (United States)
Sarinnapha Vasunilashorn, Univ. of California/Los Angeles (United States)
Eric Kleerup, Univ. of California/Los Angeles (United States)
Jonathan Goldin M.D., Univ. of California/Los Angeles (United States)

Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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