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Computer reconstruction of a human lung boundary model from magnetic resonance images.

A mathematical description of the morphology of the lung is necessary for modeling and analyzing the deposition of inhaled aerosols A model of the lung boundary was generated from magnetic resonance images, with the goal of creating a framework for anatomically realistic morphological models of the...

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Published in:Respiratory Care Vol. 49; no. 2; pp. 180 - 186
Main Authors: Burton RT, Isaacs KK, Fleming JS, Martonen TB
Format: diagnostic images pictorial research Journal Article
Published: Mary Ann Liebert, Inc. 2004 Feb
Online Access:View this record in EBSCOhost
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      dt: 2004 Feb
      vid: 49
      iid: 2
      pid: 1365
      pub: Mary Ann Liebert, Inc.
      place: New Rochelle, New York
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        atl: Computer reconstruction of a human lung boundary model from magnetic resonance images.
      aug:
        au:
          Burton RT
          Isaacs KK
          Fleming JS
          Martonen TB
        affil: Science Applications International Corporation, Research Triangle Park, NC
      sug:
        subj:
          Computer Simulation
          Lung
          Magnetic Resonance Imaging
          Models, Anatomic
          Adult
          Aerosols
          Data Analysis Software
          Funding Source
          Male
          Tomography, Emission-Computed, Single-Photon
          Human
          Adult: 19-44 years
          Male
      ab: A mathematical description of the morphology of the lung is necessary for modeling and analyzing the deposition of inhaled aerosols A model of the lung boundary was generated from magnetic resonance images, with the goal of creating a framework for anatomically realistic morphological models of the human airway network. We used data visualization and analysis software to reconstruct the lung volume from a series of transverse magnetic resonance images collected at many vertical locations in the lung, ranging from apex to base. The lung model was then built using isosurface extraction techniques. These modeling methods may facilitate the creation of customized morphological models for individual subjects, resulting in improved interpretation of aerosol distribution data from single-photon-emission computed tomography (SPECT). Such customized models could be developed for children and for patients with respiratory diseases, thus aiding in the study of inhaled medications and environmental aerosols in these populations.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        pictorial
        research
        Journal Article
      ougenre: Article
    language: English
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