Z-Normalize
This node normalizes the input using the z-score (or standard score). The z-score is calculated by subtracting the mean and dividing by the standard deviation.
The mean and standard deviation can be calculated from the entire ND-image, per 3D-volume or per slice. These values can also be constrained within an optional input mask.
The standard deviation \(s\) is calculated using the following equation:
where \(x_i\) are individual data points, \(N\) is the total numer of data ponts, \(\bar{x}\) is the sample mean, and \(^*\) is the complex conjugate which only affects complex data.
Inputs
Input
Input data to be normalized.
Type: Image, List, Required, Single
Mask
Optional mask that defines the region from which the mean and standard deviation are calculated.
Type: Mask, Optional, Single
Outputs
Output
Normalized output, of the same type as the input.
Type: Image, List
Settings
Normalize Selection
Specify how the normalization should be performed:
Per Slice: Normalizes each slice independently.
Per Volume: Normalizes each 3D volume independently.
Entire Image: Normalizes the entire ND-image as a whole.
Values: Per Slice, Per Volume, Entire Image
See also
Keywords:
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