Multi-feature Intensity Inhomogeneity Correction in MR Images

Abstract

In MRI, image intensity inhomogeneity is an adverse phenomenon that increases inter-tissue overlapping and hampers quantitative analysis. This study provides a powerful fully automated intensity inhomogeneity correction method that makes no a prior assumptions on the image intensity distribution and is able to correct intensity inhomogeneity with high dynamics. Besides using intensity features, as in most of the existing methods, spatial image features are also incorporated into the correction algorithm. A force is computed in each image point so that distribution of multiple features will shrink in the direction of intensity feature. Extensive regularization of those forces produces smooth inhomogeneity correction estimate, which is gradually improved in an iterative correction framework. The method was tested on simulated and real MR images for which gold standard segmentations were available. The results showed that the method was successful on uniform as well as on low and highly dynamic intensity uniformity images.