Image analysis – Image segmentation
Reexamination Certificate
2006-08-23
2008-09-09
Johns, Andrew W. (Department: 2624)
Image analysis
Image segmentation
C382S217000
Reexamination Certificate
active
07424153
ABSTRACT:
This invention relates to shape priors for level set representations. An embodiment of the invention comprises a first stage and a second stage. In the first stage, a shape model can be built directly on level set space using a collection of samples. The shape model can be constructed using a variational framework to create a non-stationary pixel-wise model that accounts for shape variabilities. Then, in the second stage, the shape model can be used as basis to introduce the shape prior in an energetic form. In terms of level set representations, the shape prior aims at minimizing non-stationary distance between the evolving interface and the shape model. An embodiment according to the present invention can be integrated with an existing, data-driven variational method to perform image segmentation for physically corrupted and incomplete data.
REFERENCES:
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Adalsteinsson et al., “A Fast Level Set Method for Propagating Interfaces,” Journal of Computational Physics, vol. 118, 1995, pp. 269-277.
Paragios Nikolaos
Rousson Mikael
Johns Andrew W.
Paschburg Donald B.
Siemens Corporate Research Inc.
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