Segmentation

This category contains 7 operator(s).

class BinaryThreshold

Binary Threshold

Threshold image. Voxels with values between minimum and maximum intensities will be considered object, others background.

transform(self, dataset, lower_threshold=40.0, upper_threshold=255.0)
Parameters

  • lower_threshold (double)

    • default: 40.0

  • upper_threshold (double)

    • default: 255.0

Child Datasets

  • thresholded_segmentation (label_map) - Thresholded Segmentation

Implementation

  • Python script: BinaryThreshold.py

  • JSON descriptor: BinaryThreshold.json

class LabelObjectAttributes

Label Object Attributes

Creates a child dataset containing attributes of labeled objects in a labeled dataset. The input dataset is unmodified.

Note

This operator is not compatible with external Python execution.

transform(self, dataset)
Results

  • component_statistics (table) - Component Statistics

Implementation

  • Python script: LabelObjectAttributes.py

  • JSON descriptor: LabelObjectAttributes.json

class LabelObjectDistanceFromPrincipalAxis

Label Object Distance From Principal Axis

Computes the distance from an axis to voxels with the chosen label. The dataset is expected to be a label map and have field data arrays named ‘Center’ and ‘PrincipalAxes’. Distance values replace labels in the dataset.

Note

This operator is not compatible with external Python execution.

transform(self, dataset, label_value=1, principal_axis=0)
Parameters

  • label_value (int) - Label value of voxels for which distance should be computed.

    • default: 1

  • principal_axis (enumeration) - Principal axis to use

    • default: 0

    • options:

      • 0 - First

      • 1 - Second

      • 2 - Third

Implementation

  • Python script: LabelObjectDistanceFromPrincipalAxis.py

  • JSON descriptor: LabelObjectDistanceFromPrincipalAxis.json

class LabelObjectPrincipalAxes

Label Object Principal Axes

Computes principal axes of a labeled object using principal components analysis of the positions of the labeled voxels. This data transform causes no changes in the dataset voxels, but it does save the principal axes and center of the label object.

Note

This operator is not compatible with external Python execution.

transform(dataset, label_value=1)
Parameters

  • label_value (int)

    • default: 1

Implementation

  • Python script: LabelObjectPrincipalAxes.py

  • JSON descriptor: LabelObjectPrincipalAxes.json

class OtsuMultipleThreshold

Otsu Multiple Threshold

Use Otsu multiple threshold algorithm to automatically determine thresholds separating voxels into different classes based on image intensity.

Note

This operator is not compatible with external Python execution.

transform(self, dataset, number_of_thresholds=1, enable_valley_emphasis=False)
Parameters

  • number_of_thresholds (int)

    • default: 1

    • minimum: 1

  • enable_valley_emphasis (bool)

    • default: False

Child Datasets

  • label_map (label_map) - Label Map

Implementation

  • Python script: OtsuMultipleThreshold.py

  • JSON descriptor: OtsuMultipleThreshold.json

class SegmentParticles

Segment Particles

Segment spherical particles from a homogeneous, dark background. Even if the particles have pores, they are segmented as solid structures.

Note

This operator is not compatible with external Python execution.

transform(self, dataset, minimum_radius=4)
Parameters

  • minimum_radius (int)

    • default: 4

    • minimum: 1

Child Datasets

  • label_map (label_map) - Label Map

Implementation

  • Python script: SegmentParticles.py

  • JSON descriptor: SegmentParticles.json

class SegmentPores

Segment Pores

Segment pores. The expected pore size must greater than the minimum radius and less than the maximum radius. Pores will be separated according to the minimum radius.

Note

This operator is not compatible with external Python execution.

transform(self, dataset, minimum_radius=0.5, maximum_radius=6.)
Parameters

  • minimum_radius (double)

    • default: 0.5

    • minimum: 0.0

  • maximum_radius (double)

    • default: 6.0

    • minimum: 0.0

Child Datasets

  • label_map (label_map) - Label Map

Implementation

  • Python script: SegmentPores.py

  • JSON descriptor: SegmentPores.json