Z-Normalize

Node Icon

Normalizes input using the z-score (or standard score). It is calculated by subtracting the mean and then dividing the difference by the standard deviation.

For Image inputs, the mean and standard deviation can be calculated from the entire ND-image, per 3D-volume or per slice.

The standard deviation \(s\) is computed using

\[ s = \sqrt{\frac{1}{N-1}\sum_ {i=1}^N{(x_i-\bar{x})(x_i-\bar{x})^{*}}} \]

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.

Type: Image, Numeric Array, Column, List, Required, Single

Outputs

Output

Output, the same type as the input.

Type: Image, Numeric Array, Column, List

Settings

Normalize Selection

Set how to perform the normalization:
Per Slice normalizes each slice separately
Per Volume normalizes each 3D-volume separatly
Entire Image normalizes the entire ND-image.

Values: Per Slice, Per Volume, Entire Image