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Mean Shift Gradient Vector Flow: A Robust External Force Field for 3D Active Surfaces

IEEE International Conference on Pattern Recognition: 2784-2787, 2010
Download the publication : MSGVF_paper.pdf [2.2Mo]   MSGVF_talk.pdf [8.2Mo]  

Abstract: Gradient vector flow snakes are a very common method in bio-medical image segmentation. The use of gradient vector flow herein brings some major advantages like a large capture range and a good adaption of the snakes in concave regions. In some cases though, the application of gradient vector flow can also have undesired effects, e.g. if only parts of an image are strongly blurred, the remaining weak gradients will be smoothed away. Also, large gradients resulting from small but bright image structures usually have strong impact on the overall result. To tackle this problem, we present an improvement of the gradient vector flow, using the mean shift procedure and show its advantages on the segmentation of 3D cell nuclei.

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BibTex references

@InProceedings{KBR10,
  author       = "M.Keuper and J.Padeken and P.Heun and H.Burkhardt and O.Ronneberger",
  title        = "Mean Shift Gradient Vector Flow: A Robust External Force Field for 3D Active Surfaces",
  booktitle    = "IEEE International Conference on Pattern Recognition",
  pages        = "2784-2787",
  year         = "2010",
  url          = "http://lmb.informatik.uni-freiburg.de//Publications/2010/KBR10"
}

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