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Efficient and Robust Segmentations Based on Eikonal and Diffusion PDEs

  • Bertrand Peny
  • Gozde Unal
  • Greg Slabaugh
  • Tong Fang
  • Christopher Alvino
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4153)

Abstract

In this paper, we present efficient and simple image segmentations based on the solution of two separate Eikonal equations, each originating from a different region. Distance functions from the interior and exterior regions are computed, and final segmentation labels are determined by a competition criterion between the distance functions. We also consider applying a diffusion partial differential equation (PDE) based method to propagate information in a manner inspired by the information propagation feature of the Eikonal equation. Experimental results are presented in a particular medical image segmentation application, and demonstrate the proposed methods.

Keywords

Distance Function Minimal Path Gradient Magnitude Eikonal Equation Exterior Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bertrand Peny
    • 1
  • Gozde Unal
    • 1
  • Greg Slabaugh
    • 1
  • Tong Fang
    • 1
  • Christopher Alvino
    • 2
  1. 1.Intelligent Vision and ReasoningSiemens Corporate ResearchPrincetonUSA
  2. 2.Section of Biomedical Image Analysis, Department of RadiologyUniversity of PennsylvaniaPhiladelphiaUSA

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