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Semi-automatic segmentation algorithm for pet oncology images

  • US 7,006,677 B2
  • Filed: 04/15/2002
  • Issued: 02/28/2006
  • Est. Priority Date: 04/15/2002
  • Status: Expired due to Fees
First Claim
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1. A method for segmenting three-dimensional (3D) medical images containing a region of interest, the method comprising the steps of:

  • identifying a first set of seed points within the region of interest;

    identifying a second set of seed points outside the region of interest;

    constructing a first sphere within the region of interest centered around the first set of seed points;

    classifying voxels contained within 3D medical images using a spatial constrained fuzzy clustering algorithm whereby transforming the voxels contained within the 3D medical image into a fuzzy partition domain based on a homogeneity function;

    successively generating a plurality of second spheres about said first sphere;

    accepting ones of the plurality of second spheres that satisfy the homogeneity function threshold as defined by the spatial constricted fuzzy clustering algorithm;

    adaptively growing a three-dimensional area defining the region of interest based on the step of accepting; and

    displaying the region of interest defined by the step of adaptively growing.

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