Z-Normalize

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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:

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

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 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