Bias Field Correction
The nonparametric nonuniform intensity normalization (N3) algorithm, as introduced by Sled et al. in 1998 is a method for correcting nonuniformity associated with MR images. The algorithm assumes a simple parametric model (Gaussian) for the bias field and does not require tissue class segmentation. In addition, there are only a couple of parameters to tune with the default values performing quite well.
The N4 algorithm is a variation of the original N3 algorithm with the additional benefits of an improved B-spline fitting routine which allows for multiple resolutions to be used during the correction process.
Type: Image4DFloat, Required, Single
Image to use as mask.
Type: Image4DBool, Optional, Single
An approximation of the bias field.
Convergence Threshold Number
Set the convergence threshold. Convergence is determined by the coefficient of variation of the difference image between the current bias field estimate and the previous estimate. If this value is less than the specified threshold, the algorithm proceeds to the next fitting level or terminates if it is at the last level.
Field Width at Half Maximum Number
Set the full width at half maximum parameter characterizing the width of the Gaussian deconvolution. Default = 0.15.
Number of Control Points Integer
Set the control point grid size defining the B-spline estimate of the scalar bias field. In each dimension, the B-spline mesh size is equal to the number of control points in that dimension minus the spline order. Default = 4 control points in each dimension for a mesh size of 1 in each dimension.
Number of Histogram Bins Integer
Set number of bins defining the log input intensity histogram. Default = 200.
Spline Order Integer
Set the spline order defining the bias field estimate. Default = 3.
Wiener Filter Noise Number
Set the noise estimate defining the Wiener filter. Default = 0.01.
If set the filter will downsample the image before calculating the bias field, this is recommended.
Shrink Factor Integer
The shrink factor for the downsample.
Upsample Interpolator Selection
The interpolator to use when upsampling the resulting bias field before applying it to the original image.
Values: NearestNeighbour, Linear, BSpline, Gaussian, BlackmanWindowedSinc, CosineWindowedSinc, HammingWindowedSinc, LanczosWindowedSinc, WelchWindowedSinc
- Tustison N., Gee J. N4ITK: Nick's N3 ITK Implementation For MRI Bias Field Correction. 2010 Dec.
- J.G. Sled, A.P. Zijdenbos and A.C. Evans. ‘A Nonparametric Method for Automatic Correction of Intensity Nonuniformity in Data’ IEEE Transactions on Medical Imaging, Vol 17, No 1. Feb 1998.
- N.J. Tustison, B.B. Avants, P.A. Cook, Y. Zheng, A. Egan, P.A. Yushkevich, and J.C. Gee. ‘N4ITK: Improved N3 Bias Correction’ IEEE Transactions on Medical Imaging, 29(6):1310-1320, June 2010.
- “The Insight Segmentation and Registration Toolkit” www.itk.org
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