Coupling level set model for brain MR image segmentation and bias field correction
脑MR图像分割和偏移场矫正的耦合水平集模型

Due to the correction of the bias field,it is hard to obtain the accurate segmentation results of magnetic resonance(MR) images using traditional methods.In this paper,a set of basis functions is constructed firstly to fit the smoothness bias field;then the information of the bias field is introduced to the Gaussian density function,and according to the statistics classification rule,we define the energy function for the brain MR image segmentation and bias field correction.At last,this energy function is incorporated into a three-phase level set framework to propose our model.Compared with other approaches,our experiments demonstrate that our method not only can obtain accurate segmentation results but also can restore images better.