flood#

flood(im, labels, mode: Literal['maximum', 'minimum', 'median', 'mean', 'size', 'standard_deviations', 'variance'] = 'max')[source]#

Floods/fills each region in an image with a single value based on the specific values in that region.

This function calls the various functions in scipy.ndimage.measurements but instead of returning a list of values, it fills each region with its value. This is useful for visualization and statistics.

Parameters:

im (array_like) – An image with the numerical values of interest in each voxel, and 0’s elsewhere.
labels (array_like) – An array the same shape as im with each region labeled.
mode (string) –
Specifies how to determine the value to flood each region. Options taken from the scipy.ndimage.measurements functions:

’maximum’
Floods each region with the local max in that region. The keyword max is also accepted.

’minimum’
Floods each region the local minimum in that region. The keyword min is also accepted.

’median’
Floods each region the local median in that region

’mean’
Floods each region the local mean in that region

’size’
Floods each region with the size of that region. This is actually accomplished with scipy.ndimage.sum by converting im to a boolean image (im = im > 0).

’standard_deviation’
Floods each region with the value of the standard deviation of the voxels in im.

’variance’
Floods each region with the value of the variance of the voxels in im.

Returns:

flooded – A copy of im with new values placed in each forground voxel based on the mode.

Return type:

ndarray