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Branch‐Based Model for the Diameters of the Pulmonary Airways: Accounting for Departures From Self‐Consistency and Registration Errors
Authors:Moni B. Neradilek  Nayak L. Polissar  Daniel R. Einstein  Robb W. Glenny  Kevin R. Minard  James P. Carson  Xiangmin Jiao  Richard E. Jacob  Timothy C. Cox  Edward M. Postlethwait  Richard A. Corley
Affiliation:1. The‐Mountain‐Whisper‐Light Statistics, Seattle, WashingtonFax: 206‐524‐7282.;2. The‐Mountain‐Whisper‐Light Statistics, Seattle, Washington;3. Pacific Northwest National Laboratory, Richland, Washington;4. Division of Pulmonary and Critical Care Medicine, School of Medicine, University of Washington, Seattle, Washington;5. Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York;6. Department of Pediatrics, University of Washington, Seattle, Washington;7. Department of Environmental Health Sciences, University of Alabama, Birmingham, Alabama
Abstract:We examine a previously published branch‐based approach for modeling airway diameters that is predicated on the assumption of self‐consistency across all levels of the tree. We mathematically formulate this assumption, propose a method to test it and develop a more general model to be used when the assumption is violated. We discuss the effect of measurement error on the estimated models and propose methods that take account of error. The methods are illustrated on data from MRI and CT images of silicone casts of two rats, two normal monkeys, and one ozone‐exposed monkey. Our results showed substantial departures from self‐consistency in all five subjects. When departures from self‐consistency exist, we do not recommend using the self‐consistency model, even as an approximation, as we have shown that it may likely lead to an incorrect representation of the diameter geometry. The new variance model can be used instead. Measurement error has an important impact on the estimated morphometry models and needs to be addressed in the analysis. Anat Rec,, 2012. © 2012 Wiley Periodicals, Inc.
Keywords:morphometry  pulmonary airway tree  self‐similarity
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