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This node performs pixelwise voting among an arbitrary number of input Masks, where each of them represents a segmentation of the same scene (i.e., image). Voting is a simple method of classifier combination applied to image segmentation.

Each output pixel contains the value (TRUE or FALSE) that occurred most often among the values assigned to this pixel in all the input volumes, that is, the value that received the maximum number of “votes” from the input pixels.



Input list of masks containing segmentations of the same object. Must contain at least two masks of the same size.

Type: Mask, List, Required, Single



Mask with the result of the voting.

Type: Mask


Analysis Selection

Within List assumes that the input is a list containing segmentations of the same object, and performs the analysis within the input list.

Across Lists assumes that there are at least two corresponding list inputs, where element n in each list are segmentations of the same object and performs the analysis across lists.

Values: Within List, Across Lists

Include Undecided Voxels Boolean

Set undecided voxels to true or false.

See also