• DocumentCode
    1115693
  • Title

    A Hybrid Eulerian–Lagrangian Approach for Thickness, Correspondence, and Gridding of Annular Tissues

  • Author

    Rocha, Kelvin R. ; Yezzi, Anthony J., Jr. ; Prince, Jerry L.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA
  • Volume
    16
  • Issue
    3
  • fYear
    2007
  • fDate
    3/1/2007 12:00:00 AM
  • Firstpage
    636
  • Lastpage
    648
  • Abstract
    We present a novel approach to efficiently compute thickness, correspondence, and gridding of tissues between two simply connected boundaries. The solution of Laplace´s equation within the tissue region provides a harmonic function whose gradient flow determines the correspondence trajectories going from one boundary to the other. The proposed method uses and expands upon two recently introduced techniques in order to compute thickness and correspondences based on these trajectories. Pairs of partial differential equations are efficiently computed within an Eulerian framework and combined with a Lagrangian approach so that correspondences trajectories are partially constructed when necessary. Examples are presented in order to compare the performance of this method with those of the pure Lagrangian and pure Eulerian approaches. Results show that the proposed technique takes advantage of both the speed of the Eulerian approach and the accuracy of the Lagrangian approach
  • Keywords
    Laplace equations; biological tissues; medical image processing; Laplace equation; annular tissue gridding; correspondence trajectories; gradient flow; harmonic function; hybrid Eulerian-Lagrangian approach; partial differential equations; Alzheimer´s disease; Cardiac disease; Cerebral cortex; Computed tomography; Heart; Lagrangian functions; Laplace equations; Magnetic resonance imaging; Myocardium; Partial differential equations; Correspondence; correspondence trajectory; partial differential equations (PDEs); thickness; Algorithms; Artificial Intelligence; Heart; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Models, Cardiovascular; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2007.891072
  • Filename
    4099404