Preventing Signal Degradation During Elastic Matching of Noisy DCE-MR Eye Images

  • Kishore Mosaliganti
  • Guang Jia
  • Johannes Heverhagen
  • Raghu Machiraju
  • Joel Saltz
  • Michael Knopp
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)


Motion during the acquisition of dynamic contrast enhanced MRI can cause model-fitting errors requiring co-registration. Clinical implementations use a pharmacokinetic model to determine lesion parameters from the contrast passage. The input to the model is the time-intensity plot from a region of interest (ROI) covering the lesion extent. Motion correction meanwhile involves interpolation and smoothing operations thereby affecting the time-intensity plots. This paper explores the trade-offs in applying an elastic matching procedure on the lesion detection and proposes enhancements. The method of choice is the 3D realization of the Demon’s elastic matching procedure. We validate our enhancements using synthesized deformation of stationary datasets that also serve as ground-truth. The framework is tested on 42 human eye datasets. Hence, we show that motion correction is beneficial in improving the model-fit and yet needs enhancements to correct for the intensity reductions during parameter estimation.


Pharmacokinetic Model Motion Correction Dynamic Contrast Histogram Match Slice Location 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kishore Mosaliganti
    • 1
  • Guang Jia
    • 2
  • Johannes Heverhagen
    • 2
  • Raghu Machiraju
    • 1
  • Joel Saltz
    • 3
  • Michael Knopp
    • 2
  1. 1.Department of Computer Science and EngineeringThe Ohio State UniversityColumbusUSA
  2. 2.Department of RadiologyThe Ohio State UniversityColumbusUSA
  3. 3.Department of Biomedical InformaticsThe Ohio State UniversityColumbusUSA

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