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
Normalization (sociology)Nonparametric statisticsMultiplicative functionIntensity (physics)Computer scienceAlgorithmArtificial intelligencePattern recognition (psychology)MathematicsStatisticsPhysicsOpticsMathematical analysis
Affiliated Institutions
Related Publications
New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0
PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasona...
Surface Enhanced Raman Spectroscopy of Individual Rhodamine 6G Molecules on Large Ag Nanocrystals
To explore the relationship between local electromagnetic field enhancement and the large SERS (surface enhanced Raman scattering) enhancement that enables the observation of si...
Improving Bayesian Population Dynamics Inference: A Coalescent-Based Model for Multiple Loci
Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-b...
Linear Smoothers and Additive Models
We study linear smoothers and their use in building nonparametric regression models. In the first part of this paper we examine certain aspects of linear smoothers for scatterpl...
Smooth Skyride through a Rough Skyline: Bayesian Coalescent-Based Inference of Population Dynamics
Kingman's coalescent process opens the door for estimation of population genetics model parameters from molecular sequences. One paramount parameter of interest is the effective...
Publication Info
- Year
- 1998
- Type
- article
- Volume
- 17
- Issue
- 1
- Pages
- 87-97
- Citations
- 4745
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
4745
OpenAlex
Cite This
John G. Sled,
Alex Zijdenbos,
Alan C. Evans
(1998).
A nonparametric method for automatic correction of intensity nonuniformity in MRI data.
IEEE Transactions on Medical Imaging
, 17
(1)
, 87-97.
https://doi.org/10.1109/42.668698
Identifiers
- DOI
- 10.1109/42.668698