A New Stochastic Model-Based Image Segmentation Technique For X-Ray CT Image

This manuscript demonstrates that X-ray CT image can be modeled by a finite normal mixture. The number of image classes in the observed image is detected by the information criteria (AIC or MDL). Parameters of the model are estimated by a modified K-mean algorithm and Bayesian decision criterion is the basis for this image segmentation approach. The use of simulated and real image data demonstrate the very promising results of this proposed technique.