A regularized estimation method for MR inhomogeneity correction

Magnetic resonance imaging is affected by intensity inhomogeneity, also known as the bias field, which is mainly caused by imperfections in the radio frequency coils or inhomogeneous coil sensitivities in the receiving coils. In this paper, we proposed a new method which automatically correct the bias field using a regularized method. The method does not need extra scan devices or empirical data. This method includes minimizing a cost function containing both a data-fit term and a regularization term, which provide robust inhomogeneity estimates. The method choose a region in which the intensities are similar and then use a low-pass filter and a regularized polynomial fitting method to estimate the bias field. The method has been evaluated with both simulated data and real clinical data and the results indicate that this method achieves excellent performance in estimating the intensity inhomogeneities.