• DocumentCode
    794649
  • Title

    An Eulerian PDE approach for computing tissue thickness

  • Author

    Yezzi, Anthony J., Jr. ; Prince, Jerry L.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    22
  • Issue
    10
  • fYear
    2003
  • Firstpage
    1332
  • Lastpage
    1339
  • Abstract
    We outline an Eulerian framework for computing the thickness of tissues between two simply connected boundaries that does not require landmark points or parameterizations of either boundary. Thickness is defined as the length of correspondence trajectories, which run from one tissue boundary to the other, and which follow a smooth vector field constructed in the region between the boundaries. A pair of partial differential equations (PDEs) that are guided by this vector field are then solved over this region, and the sum of their solutions yields the thickness of the tissue region. Unlike other approaches, this approach does not require explicit construction of any correspondence trajectories. An efficient, stable, and computationally fast solution to these PDEs is found by careful selection of finite differences according to an up-winding condition. The behavior and performance of our method is demonstrated on two simulations and two magnetic resonance imaging data sets in two and three dimensions. These experiments reveal very good performance and show strong potential for application in tissue thickness visualization and quantification.
  • Keywords
    biological tissues; biomedical MRI; finite difference methods; medical image processing; partial differential equations; thickness measurement; vectors; Eulerian PDE approach; correspondence trajectories length; magnetic resonance imaging; magnetic resonance imaging data sets; medical diagnostic imaging; numerical methods; tissue region thickness; tissue thickness computation; tissue thickness quantification; tissue thickness visualization; up-winding condition; Alzheimer´s disease; Biomedical imaging; Cardiac disease; Computational modeling; Data visualization; Finite difference methods; Image analysis; Magnetic resonance imaging; Myocardium; Partial differential equations; Algorithms; Anatomy, Cross-Sectional; Anthropometry; Cartilage, Articular; Cerebral Cortex; Computer Simulation; Connective Tissue; Heart; Humans; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Models, Biological; Pattern Recognition, Automated; Phantoms, Imaging; Tibia;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2003.817775
  • Filename
    1233930