An Energy Minimization Approach to the Data Driven Editing of Presegmented Images/Volumes

  • Leo Grady
  • Gareth Funka-Lea
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)


Fully automatic, completely reliable segmentation in medical images is an unrealistic expectation with today’s technology. However, many automatic segmentation algorithms may achieve a near-correct solution, incorrect only in a small region. For these situations, an interactive editing tool is required, ideally in 3D, that is usually left to a manual correction. We formulate the editing task as an energy minimization problem that may be solved with a modified version of either graph cuts or the random walker 3D segmentation algorithms. Both algorithms employ a seeded user interface, that may be used in this scenario for a user to seed erroneous voxels as belonging to the foreground or the background. In our formulation, it is unnecessary for the user to specify both foreground and background seeds.


Random Walker Editing Tool Shape Prior Energy Minimization Problem Random Walker Algorithm 
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

  • Leo Grady
    • 1
  • Gareth Funka-Lea
    • 1
  1. 1.Department of Imaging and VisualizationSiemens Corporate ResearchPrincetonUSA

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