Segmentation of MR brain images with bias artifact

Brain MR Images corrupted by RF- Inhomogeneity (bias artifact) exhibit brightness variations across the image. As a consequence, a standard Fuzzy C-Means (fern) segmentation algorithm may fail. In this work we show a new general-purpose bias removing algorithm, which can be used as a pre-processing step for a fern segmentation. We also compare our experimental results with the ones achieved by using E2 D - H U M filter, showing an improvement in brain segmentation and bias removal.