A Region Based Variational Method for Image Segmentation and Bias Correction with Application to MRI

This paper implements a region-based method for image segmentation, which is able to deal with intensity inhomogeneities in the segmentation. First, based on the MRI image model with bias error in it we derive local intensity clustering property of the image intensities, and define a local clustering criterion function for the image intensities in a neighborhood of each point. In a level set formulation, this criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, by minimizing this energy, our method is able to simultaneously segment the image and estimate the bias field, and the estimated bias field can be used for bias correction. Post Enhancement is applied to improve the contrast and brightness which increases the SNR. In this paper, the performance is evaluated using the plots for SNR, MSE (Mean Square Error).