## Module: AutoThresholdForMultiThresholding (
)

### Description:

> This is an experimental module from the Xtra Library: https://xtras.amira-avizo.com.

> To be able to create a precise surface without additional smoothing using Generate Surface, segmentation with Multi-Thresholding is necessary. But there the user has to interactively set the threshold value(s).

> This Tcl script-object calls Auto Thresholding for automatic and reproducible determination of the threshold value(s), and uses them with Multi-Thresholding.

> The created label-field contains the weight values necessary for using Generate Surface with the smoothing option "Existing Weights".

> The settings of the module are a sub-set of those from Auto Thresholding and Multi-Thresholding.

### Connections:

> Input Image `[required]`
> The image to be thresholded. Supported types include: Grayscale images (Uniform Scalar Field).

### Ports:

> Type
> This port allows selecting the configuration of this module. The available configurations are:
> Auto Segment 3 Phases,
> Auto Threshold High,
> Auto Threshold Low.

> Mode
> This port allows defining the following modes for auto thresholding computation:

> "min-max": the threshold is searched between the minimum and maximum of the input image intensities.
> "other": the threshold is searched between the values set in the Input Range port.

> Input Range
> This port defines a range where the threshold level will be defined by the chosen criterion before being used on the whole data range following the chosen configuration.
> For example, it is useful if your data contains a lot of noise on one value: if you exclude this value from the range the value will be ignored from the threshold level definition and can improve your result.
> Note: this port is unused if the port Mode is set to min-max.

> Criterion
> This option refers to the measure of dispersion used in the algorithm. The variance yields better results in most cases.
> Entropy: Entropy of the intensity distribution.
> Factorisation: Variance of the intensity distribution.
> Moments: Moments of the intensity distribution.
> IsoData: Iterative global thresholding algorithm which is based on the gray value histogram of the data.

> Options
> Toggle subvoxel accuracy causes certain weights to be computed, indicating the degree of confidence of the assignment of a voxel to a particular region. This information is used by the surface reconstruction algorithm to create smooth boundary surfaces, see the Generate Surface module. If no weights are present quite blocky surfaces occur. Note that weights can also be defined using the smoothing filter of the Segmentation Workroom .
> The second option remove couch will detect the biggest connected component of voxels not assigned to the first region, i.e., Exterior and assign them to the Exterior.
> Finally, if option remove bubbles is set an algorithm similar to remove couch is applied in order to detect bubbles inside the Exterior. Because of their low intensity values otherwise these regions would be assigned to Exterior.