Compensation of MRI T1-weighted spin-echo images for radio-frequency inhomogeneities

We propose a correction method for magnetic resonance (MR) images to eliminate the effects of the inhomogeneity of the radio-frequency (RF) pulses and of the sensivity of the RF reception particularly in the case of T₁-weighted images. In this case the effects of the pulse inhomogeneities vary with the tissues, which prevents the use of simpler correction techniques based on a global multiplicative bias field model. Here, the MR signal is modeled as a sum of contributions of all the tissues present in the object. For sake of generality, each pixel is assumed to contain an unknown proportion of each tissue, so that the usually adopted segmentation based approach is not valid in the present context. The number of tissues composing the object as well as the MR characteristics of each tissue are required. Several images with different acquisition parameter values are also needed. A penalized least-square criterion is proposed to estimate the RF emitted field, the RF sensitivity reception and the proportion of each tissue. The criterion contains smoothness regularization for both RF fields. We solve the optimization problem using a conjugate gradient algorithm within a Gauss-Seidel iterative scheme. Results based on real MR images of fish demonstrate the effectiveness of the method.