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.
Ardizzone, E., Pirrone, R., Gambino, O., Alagna, F. (2010). Segmentation of MR brain images with bias artifact. In 9th International Conference on Information Technology and Applications in Biomedicine 2009 (ITAB 2009) (pp.1-4). Los Alamitos, CA : IEEE Computer Society [10.1109/ITAB.2009.5394449].
Segmentation of MR brain images with bias artifact
ARDIZZONE, Edoardo;PIRRONE, Roberto;GAMBINO, Orazio;
2010-01-01
Abstract
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.
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