detectLabelEdges

Takes a labelmap and returns an image where all pixels on label edges are set to 1 and all other pixels to 0.

Parameters

label_map : Image The label image where edges between labels will be detected. edge_image_destination : Number Binary image where edges were marked with value 1 and all other pixels will be set to 0.

Categories: Detection, Filter, Labels

Availability: Available in Fiji by activating the update sites clij and clij2. This function is part of clij2_-2.5.0.1.jar.

detectLabelEdges often follows after

extendLabelingViaVoronoi (1)

detectLabelEdges is often followed by

release (1)
dilateBox (1)

Usage in ImageJ macro

Ext.CLIJ2_detectLabelEdges(Image label_map, Image edge_image_destination);

Usage in object oriented programming languages

Java

// init CLIJ and GPU
import net.haesleinhuepf.clij2.CLIJ2;
import net.haesleinhuepf.clij.clearcl.ClearCLBuffer;
CLIJ2 clij2 = CLIJ2.getInstance();

// get input parameters
ClearCLBuffer label_map = clij2.push(label_mapImagePlus);
edge_image_destination = clij2.create(label_map);

// Execute operation on GPU
clij2.detectLabelEdges(label_map, edge_image_destination);

// show result
edge_image_destinationImagePlus = clij2.pull(edge_image_destination);
edge_image_destinationImagePlus.show();

// cleanup memory on GPU
clij2.release(label_map);
clij2.release(edge_image_destination);

Matlab

% init CLIJ and GPU
clij2 = init_clatlab();

% get input parameters
label_map = clij2.pushMat(label_map_matrix);
edge_image_destination = clij2.create(label_map);

% Execute operation on GPU
clij2.detectLabelEdges(label_map, edge_image_destination);

% show result
edge_image_destination = clij2.pullMat(edge_image_destination)

% cleanup memory on GPU
clij2.release(label_map);
clij2.release(edge_image_destination);

Icy JavaScript

// init CLIJ and GPU
importClass(net.haesleinhuepf.clicy.CLICY);
importClass(Packages.icy.main.Icy);

clij2 = CLICY.getInstance();

// get input parameters
label_map_sequence = getSequence();
label_map = clij2.pushSequence(label_map_sequence);
edge_image_destination = clij2.create(label_map);

// Execute operation on GPU
clij2.detectLabelEdges(label_map, edge_image_destination);

// show result
edge_image_destination_sequence = clij2.pullSequence(edge_image_destination)
Icy.addSequence(edge_image_destination_sequence);
// cleanup memory on GPU
clij2.release(label_map);
clij2.release(edge_image_destination);

clEsperanto Python (experimental)

import pyclesperanto_prototype as cle

cle.detect_label_edges(label_map, edge_image_destination)

Example notebooks

labelmap_voronoi
outlines_numbers_overlay
browse_operations.ipynb
voronoi_diagrams.ipynb
mesh_nearest_neighbors.ipynb
Segmentation_3D.ipynb
tissue_neighborhood_quantification.ipynb

Example scripts

labelmap_voronoi.ijm
outlines_numbers_overlay.ijm

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