• DocumentCode
    1084323
  • Title

    Modality independent elastography (MIE): a new approach to elasticity imaging

  • Author

    Washington, Chad W. ; Miga, Michael I.

  • Author_Institution
    Sch. of Med., Univ. of Mississippi, Jackson, MS, USA
  • Volume
    23
  • Issue
    9
  • fYear
    2004
  • Firstpage
    1117
  • Lastpage
    1128
  • Abstract
    The correlation between tissue stiffness and health is an accepted form of organ disease assessment. As a result, there has been a significant amount of interest in developing methods to image elasticity parameters (i.e., elastography). The modality independent elastography (MIE) method combines a nonlinear optimization framework, computer models of soft-tissue deformation, and standard measures of image similarity to reconstruct elastic property distributions within soft tissue. In this paper, simulation results demonstrate successful elasticity image reconstructions in breast cross-sectional images acquired from magnetic resonance (MR) imaging. Results from phantom experiments illustrate its modality independence by reconstructing elasticity images of the same phantom in both MR and computed tomographic imaging units. Additional results regarding the performance of a new multigrid strategy to MIE and the implementation of a parallel architecture are also presented.
  • Keywords
    biological organs; biological tissues; biomechanics; biomedical MRI; computerised tomography; deformation; diseases; elasticity; image reconstruction; medical image processing; optimisation; parallel architectures; breast cross-sectional images; computed tomographic imaging; elasticity image reconstructions; elasticity imaging; health; image similarity; magnetic resonance imaging; modality independent elastography; nonlinear optimization framework; organ disease assessment; parallel architecture; phantom experiments; soft-tissue deformation; tissue stiffness; Biological tissues; Deformable models; Diseases; Distributed computing; Elasticity; Image reconstruction; Imaging phantoms; Magnetic resonance imaging; Measurement standards; Optimization methods; Algorithms; Breast; Breast Neoplasms; Computer Simulation; Elasticity; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Models, Biological; Phantoms, Imaging; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2004.830532
  • Filename
    1327691