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CLIJ 1/2/x reference in category ‘segmentation’

This reference contains all methods currently available in CLIJ, CLIJ2 and CLIJx for segmenting images.. Read more about CLIJs release cycle

Please note: CLIJ is deprecated. Make the transition to CLIJ2.

Method is available in CLIJ (deprecated release)
Method is available in CLIJ2 (stable release)
Method is available in CLIJx (experimental release)
Method is available in clEsperanto (experimental)

Categories: Binary, Filter, Graphs, Labels, Math, Matrices, Measurements, Projections, Transformations, Detection, CLIc

[A],[B], C, D, E, F,[G], H, I, J,[K], L,[M], N, O, P, Q, R,[S],[T], U,[V],[W], X, Y, Z

A

applyWekaModel (Experimental)

Applies a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

applyWekaToTable (Experimental)

Applies a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

automaticThreshold

The automatic thresholder utilizes the threshold methods from ImageJ on a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

B

binaryWekaPixelClassifier (Experimental)

Applies a pre-trained CLIJx-Weka model to a 2D image.

G

generateFeatureStack (Experimental)

Generates a feature stack for Trainable Weka Segmentation.

generateLabelFeatureImage (Experimental)

Generates a feature image for Trainable Weka Segmentation.

K

kMeansLabelClusterer (Experimental)

Applies K-Means clustering to an image and a corresponding label map.

M

morphoLibJMorphologicalSegmentationLabelBorderImage (Experimental)

Apply MorpholibJ Morphological Segmentation to an object image to produce a label image.

morphoLibJMorphologicalSegmentationLabelObjectImage (Experimental)

Apply MorpholibJ Morphological Segmentation to an object image to produce a label image.

S

simpleITKOtsuMultipleThresholds (Experimental)

Apply SimpleITKs Otsu Multiple Thresholds to an image.

simpleITKOtsuThreshold (Experimental)

Apply SimpleITKs Otsu Thresholding to an image.

simpleITKZeroCrossing (Experimental)

Apply SimpleITKs ZeroCrossing to an image.

simpleITKZeroCrossingBasedEdgeDetection (Experimental)

Apply SimpleITKs ZeroCrossingBasedEdgeDetection to an image.

T

threshold

Computes a binary image with pixel values 0 and 1.

thresholdDefault

The automatic thresholder utilizes the Default threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdDoG (Experimental)

Applies a Difference-of-Gaussian filter to an image and thresholds it with given sigma and threshold values.

thresholdHuang

The automatic thresholder utilizes the Huang threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdIJ_IsoData

The automatic thresholder utilizes the IJ_IsoData threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdIntermodes

The automatic thresholder utilizes the Intermodes threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdIsoData

The automatic thresholder utilizes the IsoData threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdLi

The automatic thresholder utilizes the Li threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdMaxEntropy

The automatic thresholder utilizes the MaxEntropy threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdMean

The automatic thresholder utilizes the Mean threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdMinError

The automatic thresholder utilizes the MinError threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdMinimum

The automatic thresholder utilizes the Minimum threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdMoments

The automatic thresholder utilizes the Moments threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdOtsu

The automatic thresholder utilizes the Otsu threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdPercentile

The automatic thresholder utilizes the Percentile threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdRenyiEntropy

The automatic thresholder utilizes the RenyiEntropy threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdShanbhag

The automatic thresholder utilizes the Shanbhag threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdTriangle

The automatic thresholder utilizes the Triangle threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

thresholdYen

The automatic thresholder utilizes the Yen threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

trainWekaFromTable (Experimental)

Trains a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

trainWekaModel (Experimental)

Trains a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

trainWekaModelWithOptions (Experimental)

Trains a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

V

visualizeOutlinesOnOriginal (Experimental)

Combines an intensity image and a label (or binary) image so that you can see segmentation outlines on the intensity image.

W

wekaLabelClassifier (Experimental)

Applies a pre-trained CLIJx-Weka model to an image and a corresponding label map to classify labeled objects.

wekaRegionalLabelClassifier (Experimental)

Applies a pre-trained CLIJx-Weka model to an image and a corresponding label map to classify labeled objects.

38 methods listed.