## Abstract We present a method for the analysis of meta‐analytic functional imaging data. It is based on Activation Likelihood Estimation (ALE) and subsequent model‐based clustering using Gaussian mixture models, expectation‐maximization (EM) for model fitting, and the Bayesian Information Criteri
Image-based modeling of lung structure and function
✍ Scribed by Merryn H. Tawhai; Ching-Long Lin
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 459 KB
- Volume
- 32
- Category
- Article
- ISSN
- 1053-1807
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✦ Synopsis
Abstract
The current state‐of‐the‐art in image‐based modeling allows derivation of patient‐specific models of the lung, lobes, airways, and pulmonary vascular trees. The application of traditional engineering analyses of fluid and structural mechanics to image‐based subject‐specific models has the potential to provide new insight into structure–function relationships in the individual via functional interpretation that complements imaging and experimental studies. Three major issues that are encountered in studies of airflow through the bronchial airways are the representation of airway geometry, the imposition of physiological boundary conditions, and the treatment of turbulence. Here we review some efforts to resolve each of these issues, with particular focus on image‐based models that have been developed to simulate airflow from the mouth to the terminal bronchiole, and subjected to physiologically meaningful boundary conditions via image registration and soft‐tissue mechanics models. J. Magn. Reson. Imaging 2010;32:1421–1431. © 2010 Wiley‐Liss, Inc.
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