Mean Shift Gradient Vector Flow: A Robust External Force Field for 3D Active Surfaces
IEEE International Conference on Pattern Recognition: 2784-2787, 2010
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.
Images and movies
BibTex reference
@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" }