Image analysis – Image segmentation
Reexamination Certificate
2007-03-06
2007-03-06
Mancuso, Joseph (Department: 2624)
Image analysis
Image segmentation
Reexamination Certificate
active
10211779
ABSTRACT:
A method of approximating the boundary of an object in an image, the image being represented by a data set, the data set comprising a plurality of data elements, each data element having a data value corresponding to a feature of the image, the method comprising determining which one of a plurality of contours most closely matches the object boundary at least partially according to a divergence value for each contour, the divergence value being selected from the group consisting of Jensen-Shannon divergence and Jensen-Renyi divergence. Each contour Cidefines a zone ZIiand a zone ZOi, ZIirepresenting the data elements inside the contour and ZOirepresenting the data elements outside the contour, each zone having a corresponding probability distribution of data values for the data elements therein, and wherein the divergence value for each contour Cirepresents a measure of the difference between the probability distributions for the zones ZIiand ZOi. The boundary estimate is preferably a parametric contour. Further, the present invention supports the segmentation of multiple objects in a single data set simultaneously.
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Computerized Medical Systems, Inc.
Kuhn Jordan
Mancuso Joseph
Thompson & Coburn LLP
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