Medical Image Categorization Based on Gaussian Mixture Model

In this paper we present an approach for medical image categorization based on Gaussian mixture model. There are distinct differences on texture, shape and intensity characteristics among the images of different parts of body. Considering of the features of the Gaussian mixture model , first we extract the characteristic vectors of the training image set to learn the class model for each class , then categorize the test image using the Bayesian principle. The experimental results indicate that the method performs very well on CT image categorization. We achieved classification accuracy up to 97% in the experiment.