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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Vovk, U. Pernus, F. Likar, B. |
| Copyright Year | 2005 |
| Description | Author affiliation: Fac. of Electrotech. Eng., Ljubljana Univ. (Vovk, U.; Pernus, F.; Likar, B.) |
| Abstract | Intensity inhomogeneity in MR images is an undesired phenomenon, which often hampers different steps of quantitative analysis such as segmentation or registration. In this paper we propose a novel fully automated method for retrospective correction of intensity inhomogeneity. The basic assumption is that inhomogeneity correction could be improved by combining the information from multiple MR channels. Intensity inhomogeneities are simultaneously removed in a four-step iterative procedure. First, the probability distribution of intensities for two channel images is calculated. In the second step, intensity correction forces, that tend to minimize image entropies, are estimated for every image voxel. Third, inhomogeneity correction fields are obtained by regularization and normalization of all voxel forces, and last, corresponding partial inhomogeneity corrections are performed separately for each channel. The method was quantitatively evaluated on simulated and real MR brain images. The results show substantial improvement in comparison with the two state-of-the-art methods |
| Starting Page | 4290 |
| Ending Page | 4293 |
| File Size | 330903 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780387414 |
| DOI | 10.1109/IEMBS.2005.1615413 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-01-17 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Filtering Image analysis Image segmentation Anatomical structure Radio frequency Polynomials Probability distribution Entropy Brain modeling Magnetic resonance imaging |
| Content Type | Text |
| Resource Type | Article |
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