A threshold algorithms automatically (or manually) determines a threshold to distinguish between foreground and background of an image. After the threshold has been computed or manually chosen selected, the algorithm marks any pixel with an intensity value greater than this threshold with "1" and any pixel with intensity lower than the threshold as "0". The result is a binary image which subsequently can be processed with the Connected Component Analysis Node to extract a labeling with separated segments. For details see: "Survey over image thresholding techniques and quantitative performance evaluation" (Sezgin04)
This component allows the selection of dimensions of interest. If an algorithm cannot, as it only supports fewer dimensions than the number of dimensions of the image, or shouldnot, as one wants to run the algorithm only on subsets of the image, be applied on the complete image, the dimension selection can be used to define the plane/cube/hypercube on which the algorithm is applied. Example 1 with three dimensional Image (X,Y,Time): An algorithm cannot be applied to the complete image, as it only supports two dimensional images. If you select e.g. X,Y then the algorithm will be applied to all X,Y planes individually. Example 2 with three dimensional Image (X,Y,Time): The algorithm can be applied in two, three or even more dimensions. Select the dimensions to define your plane/cube/hypercube on which the algorithm will be applied.
Mode how to handle the selected column. The processed column can be added to a new table, appended to the end of the table, or the old column can be replaced by the new result
If you choose a column with a labeling here, the node will only operate on the Regions of Interests (ROIs) which are defined by the incoming labeling!
The FillingMode determines how all values, which lie outside your defined region of interest, will be set. This option is only needed if you choose a labeling column, such that the node operates on ROIs instead of the entire image. There are currently four FillingModes:
Value of Source: In this mode, pixels outside of the ROIs remain unchanged.
Minimum of Result Type: Here, values outside of the ROI are set to the smallest legal value of the output image type.
Maximum of Result Type: All values outside of the ROI are set to the largest posible value of the output image type.
No Filling: No action is taken after initializing the target image, thus all pixels outside the ROIs remain zero.
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