Abstract: Because finite mixture model for parameters estimation method partially depends on the prior assumption and is sensitive to noise in image segmentation,a non-parametric medical image B-spline density model with spatial information segmentation method was proposed in this paper.First,the image non-parametric B-spline density model was designed,and spatial information function was defined in order to make the model with spatial neighborhood information.Secondly,non-parametric B-spline expectation maximum(NNBEM) algorithm was used to estimate the unknown parameter of the density model.Finally,image was clustered according to the Bayesian criterion.This method effectively overcome the model mismatch problem,which is not only effective to deal with noisy,but also reserve edge property well.The experimental results about the simulation image segmentation show the effeciveness of this method.

Key words: Spatial information,Image segmentation,B-spline density fuction,Mixture models,Bayesian criterions