Intensity Nonuniformity Correction for Brain MR Images with Known Voxel Classes

Abstract

Intensity nonuniformity in magnetic resonance (MR) images, represented by a smooth and slowly varying function, is a typical artifact that is a nuisance for many image processing methods. To eliminate the artifact, we have to estimate the nonuniformity as a smooth and slowly varying function and factor it out from the given data. We reformulate the problem as a problem of finding a unique smooth function in a particular set of piecewise smooth functions and propose a variational method for finding it. We deliver the main idea using a simple one-dimensional example first and provide a thorough analysis of the problem in a three-phase scenario in three dimensions whose application can be found in the brain MR images. Experiments with synthetic and real MR images and a comparison with a state-of-the-art method, N3, show our algorithm's satisfactory performance in estimating the nonuniformity with and without noise. An automated procedure is also proposed for practical use.