A nonparametric method for automatic correction of intensity nonuniformity in MRI data
- 1 January 1998
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Medical Imaging
- Vol. 17 (1), 87-97
- https://doi.org/10.1109/42.668698
Abstract
A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present. The method has the advantage that it can be applied at an early stage in an automated data analysis, before a tissue model is available. Described as nonparametric nonuniform intensity normalization (N3), the method is independent of pulse sequence and insensitive to pathological data that might otherwise violate model assumptions. To eliminate the dependence of the field estimate on anatomy, an iterative approach is employed to estimate both the multiplicative bias field and the distribution of the true tissue intensities. The performance of this method is evaluated using both real and simulated MR data.Keywords
This publication has 26 references indexed in Scilit:
- Adaptive segmentation of MRI dataIEEE Transactions on Medical Imaging, 1996
- Retrospective correction of intensity inhomogeneities in MRIIEEE Transactions on Medical Imaging, 1995
- Effect of Radio Frequency Inhomogeneity Correction on the Reproducibility of Intra‐Cranial Volumes Using MR Image DataMagnetic Resonance in Medicine, 1995
- Correction of intensity variations in MR images for computer-aided tissue classificationIEEE Transactions on Medical Imaging, 1993
- Segmentation of MR Brain Images into Cerebrospinal Fluid Spaces, White and Gray MatterJournal of Computer Assisted Tomography, 1989
- Compensation for surface coil sensitivity variation in magnetic resonance imagingMagnetic Resonance Imaging, 1988
- Intensity correction in surface-coil MR imagingAmerican Journal of Roentgenology, 1987
- Comparison of linear and circular polarization for magnetic resonance imagingJournal of Magnetic Resonance (1969), 1985
- The Least-squares Fitting of Cubic Spline Surfaces to General Data SetsIMA Journal of Applied Mathematics, 1974
- Nuclear InductionPhysical Review B, 1946