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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 (fcm) 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 fcm segmentation. We also compare our experimental results with the ones achieved by using E2D-HUM filter, showing an improvement in brain segmentation and bias removal.