Automatic Segmentation Methods for Various CT Images Using Morphology Operation and Statistical Technique
Myungeun Lee, Soo-Hyung Kim, Sunworl Kim, Sung-Ryul Oh · 2007
In this paper, we present an automatic segmentation method for medical image based on the statistical technique. Here we use the morphological operations to determine automatically the number of clusters or objects composing a given image without any prior knowledge and adopt the Gaussian mixture model to mode an image statistically. Next, the deterministic annealing expectation maximization algorithm is employed to estimate the parameters of the GMM for the clustering algorithm. We apply the statistical technique for automatic segmentation of input CT image. The experimental results show that our method can segment exactly various CT images.