Medical image segmentation method and apparatus
OwnerYuan Feng, Long Huanginventors
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Abstract
A medical image segmentation method includes: step 1, initialize of the number of clusters and determine the initial values of the cluster centroids; step 2, calculate a Hausdorff distance between each cluster centroid and each pixel in the image; step 3, calculate a membership function of each pixel based on the Hausdorff distance and a Euclid distance between the cluster centroids and each pixel; step 4, calculate an objective function, cluster the pixels of the image based on the updated membership function, and update the centroid value; and repeating step 2-4, until a difference between two objective function values is less than a threshold value. Then the membership function from the last iteration is a final segmentation.
Claims9
A medical image segmentation method, which comprises the following processing steps:
- step 1, initialize the number of clusters and determine the initial values of cluster centroids;
- step 2, calculate a Pseudo-Hausdorff distance between each cluster centroid and each pixel in an image;
- step 3, calculate a membership function of each pixel being a member of a cluster based on the Pseudo-Hausdorff distance and an Euclid distance between each cluster centroid and said each pixel;
- step 4, calculate an objective function, cluster the pixels of the image based on the membership function, and update the values of the cluster centroids;
- and
- repeat step 2-4, until a difference between the objective function values of two consecutive iterations is less than a threshold value, and then the membership function from the last iteration is a final segmentation.
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