reference.md

CLIIJx-Assistant operations

This is the list of currently supported CLIJ2 and CLIJx operations.

Please note: CLIJx-Assitant is under development. Hence, this list is subject to change.

• Absolute Difference Determines the absolute difference pixel by pixel between two images.

• Absolute Computes the absolute value of every individual pixel x in a given image.

• Add Image And Scalar Adds a scalar value s to all pixels x of a given image X.

• Add Images Weighted Calculates the sum of pairs of pixels x and y from images X and Y weighted with factors a and b.

• Add Images Calculates the sum of pairs of pixels x and y of two images X and Y.

• Affine Transform2D Applies an affine transform to a 2D image.

• Affine Transform3D Applies an affine transform to a 3D image.

• Affine Transform Applies an affine transform to a 2D or 3D image

• Apply Vector Field2D Deforms an image according to distances provided in the given vector images.

• Apply Vector Field3D Deforms an image stack according to distances provided in the given vector image stacks.

• Automatic Threshold 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.

• Average Distance Of N Closest Neighbors Map Takes a label map, determines distances between all centroids and replaces every label with the average distance to the n closest neighboring labels.

• Average Neighbor Distance Map Takes a label map, determines which labels touch and replaces every label with the average distance to their neighboring labels.

• Bilateral Applies a bilateral filter using a box neighborhood with sigma weights for space and intensity to the input image.

• Binary And Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary AND operator &. All pixel values except 0 in the input images are interpreted as 1.

• Binary Edge Detection Determines pixels/voxels which are on the surface of binary objects and sets only them to 1 in the destination image. All other pixels are set to 0.

• Binary Intersection Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary intersection operator &. All pixel values except 0 in the input images are interpreted as 1.

• Binary Not Computes a binary image (containing pixel values 0 and 1) from an image X by negating its pixel values x using the binary NOT operator !

• Binary Or Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary OR operator |.

• Binary Subtract Subtracts one binary image from another.

• Binary Union Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary union operator |.

• Binary Weka Pixel Classifier Applies a pre-trained CLIJx-Weka model to a 2D image.

• Binary XOr Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary operators AND &, OR | and NOT ! implementing the XOR operator.

• Bottom Hat Box Apply a bottom-hat filter for background subtraction to the input image.

• Bottom Hat Sphere Applies a bottom-hat filter for background subtraction to the input image.

• Close Index Gaps In Label Map Analyses a label map and if there are gaps in the indexing (e.g. label 5 is not present) all subsequent labels will be relabelled.

• Closing Box Apply a binary closing to the input image by calling n dilations and n erosions subsequenntly.

• Closing Diamond Apply a binary closing to the input image by calling n dilations and n erosions subsequently.

• Combine Horizontally Combines two images or stacks in X.

• Combine Vertically Combines two images or stacks in Y.

• Concatenate Stacks Concatenates two stacks in Z.

• Connected Components Labeling Box Performs connected components analysis inspecting the box neighborhood of every pixel to a binary image and generates a label map.

• Connected Components Labeling Diamond Performs connected components analysis inspecting the diamond neighborhood of every pixel to a binary image and generates a label map.

• Convolve Convolve the image with a given kernel image.

• Copy Slice This method has two purposes: It copies a 2D image to a given slice z position in a 3D image stack or It copies a given slice at position z in an image stack to a 2D image.

• Copy Copies an image.

• Count Non Zero Pixels Slice By Slice Sphere Counts non-zero pixels in a sphere around every pixel slice by slice in a stack.

• Count Non Zero Pixels2D Sphere Counts non-zero pixels in a sphere around every pixel.

• Count Non Zero Voxels3D Sphere Counts non-zero voxels in a sphere around every voxel.

• Crop2D Crops a given rectangle out of a given image.

• Crop3D Crops a given sub-stack out of a given image stack.

• Cylinder Transform Applies a cylinder transform to an image stack assuming the center line goes in Y direction in the center of the stack.

• Detect And Label Maxima Determines maximum regions in a Gaussian blurred version of the original image.

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

• Detect Maxima2D Box Detects local maxima in a given square/cubic neighborhood.

• Detect Maxima3D Box Detects local maxima in a given square/cubic neighborhood.

• Detect Minima Box Detects local minima in a given square/cubic neighborhood.

• Detect Minima2D Box Detects local minima in a given square/cubic neighborhood.

• Detect Minima3D Box Detects local minima in a given square/cubic neighborhood.

• Difference Of Gaussian2D Applies Gaussian blur to the input image twice with different sigma values resulting in two images which are then subtracted from each other.

• Difference Of Gaussian3D Applies Gaussian blur to the input image twice with different sigma values resulting in two images which are then subtracted from each other.

• Dilate Box Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image.

• Dilate Sphere Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image.

• Divide By Gaussian Background Applies Gaussian blur to the input image and divides the original by the result.

• Divide Images Divides two images X and Y by each other pixel wise.

• Draw Distance Mesh Between Touching Labels Starting from a label map, draw lines between touching neighbors resulting in a mesh.

• Draw Mesh Between N Closest Labels Starting from a label map, draw lines between n closest labels for each label resulting in a mesh.

• Draw Mesh Between Proximal Labels Starting from a label map, draw lines between labels that are closer than a given distance resulting in a mesh.

• Draw Mesh Between Touching Labels Starting from a label map, draw lines between touching neighbors resulting in a mesh.

• Draw Touch Count Mesh Between Touching Labels Starting from a label map, draw lines between touching neighbors resulting in a mesh.

• Draw Touch Portion Mesh Between Touching Labels Starting from a label map, draw lines between touching neighbors resulting in a mesh.

• Drift Correction By Center Of Mass Fixation Determines the centerOfMass of the image stack and translates it so that it stays in a defined position.

• Drift Correction By Centroid Fixation Threshold the image stack, determines the centroid of the resulting binary image and translates the image stack so that its centroid sits in a defined position.

• Entropy Box Determines the local entropy in a box with a given radius around every pixel.

• Equal Constant Determines if an image A and a constant b are equal.

• Equal Determines if two images A and B equal pixel wise.

• Equalize Mean Intensities Of Slices Determines correction factors for each z-slice so that the average intensity in all slices can be made the same and multiplies these factors with the slices.

• Erode Box Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image.

• Erode Sphere Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image.

• Euclidean Distance From Label Centroid Map Takes a label map, determines the centroids of all labels and writes the distance of all labelled pixels to their centroid in the result image. Background pixels stay zero.

• Exclude Labels On Edges Removes all labels from a label map which touch the edges of the image (in X, Y and Z if the image is 3D).

• Exclude Labels Outside Size Range Removes labels from a label map which are not within a certain size range.

• Exclude Labels With Values Out Of Range This operation removes labels from a labelmap and renumbers the remaining labels.

• Exclude Labels With Values Within Range This operation removes labels from a labelmap and renumbers the remaining labels.

• Exponential Computes base exponential of all pixels values.

• Extend Labeling Via Voronoi Takes a label map image and dilates the regions using a octagon shape until they touch.

• Extend Labels With Maximum Radius Extend labels with a given radius.

• Extended Depth Of Focus Sobel Projection Extended depth of focus projection maximizing intensity in the local sobel image.

• Extended Depth Of Focus Tenengrad Projection Extended depth of focus projection maximizing intensity in the local sobel image.

• Extended Depth Of Focus Variance Projection Extended depth of focus projection maximizing local pixel intensity variance.

• Find Maxima Plateaus Finds local maxima, which might be groups of pixels with the same intensity and marks them in a binary image.

• Flip2D Flips an image in X and/or Y direction depending on boolean flags.

• Flip3D Flips an image in X, Y and/or Z direction depending on boolean flags.

• Gamma Correction Applies a gamma correction to an image.

• Gaussian Blur2D Computes the Gaussian blurred image of an image given two sigma values in X and Y.

• Gaussian Blur3D Computes the Gaussian blurred image of an image given two sigma values in X, Y and Z.

• Gradient X Computes the gradient of gray values along X.

• Gradient Y Computes the gradient of gray values along Y.

• Gradient Z Computes the gradient of gray values along Z.

• Greater Constant Determines if two images A and B greater pixel wise.

• Greater Or Equal Constant Determines if two images A and B greater or equal pixel wise.

• Greater Or Equal Determines if two images A and B greater or equal pixel wise.

• Greater Determines if two images A and B greater pixel wise.

• Image To Stack Copies a single slice into a stack a given number of times.

• Intensity Correction Above Threshold Otsu Determines the mean intensity of all pixel the image stack which are above a determined Threshold (Otsu et al. 1979) and multiplies it with a factor so that the mean intensity becomes equal to a given value.

• Intensity Correction Determines the mean intensity of the image stack and multiplies it with a factor so that the mean intensity becomes equal to a given value.

• Invert Computes the negative value of all pixels in a given image.

• Label Maximum Extension Map Takes a label map, determines for every label the maximum distance of any pixel to the centroid and replaces every label with the that number.

• Label Maximum Extension Ratio Map Takes a label map, determines for every label the maximum distance of any pixel to the centroid and replaces every label with the that number.

• Label Maximum Intensity Map Takes an image and a corresponding label map, determines the mean intensity per label and replaces every label with the that number.

• Label Mean Extension Map Takes a label map, determines for every label the mean distance of any pixel to the centroid and replaces every label with the that number.

• Label Mean Intensity Map Takes an image and a corresponding label map, determines the mean intensity per label and replaces every label with the that number.

• Label Minimum Intensity Map Takes an image and a corresponding label map, determines the mean intensity per label and replaces every label with the that number.

• Label Pixel Count Map Takes a label map, determines the number of pixels per label and replaces every label with the that number.

• Label Spots Transforms a binary image with single pixles set to 1 to a labelled spots image.

• Label Standard Deviation Intensity Map Takes an image and a corresponding label map, determines the standard deviation of the intensity per label and replaces every label with the that number.

• Label Surface Takes a label map and excludes all labels which are not on the surface.

• Label To Mask Masks a single label in a label map.

• Label Voronoi Octagon Takes a labelled image and dilates the labels using a octagon shape until they touch.

• Labeling Workflow A L X A segmentation workflow using maxima detection, thresholding, maximum filters and label edge detection.

• Laplace Box Applies the Laplace operator (Box neighborhood) to an image.

• Laplacian Of Gaussian3D Determined the Laplacian of Gaussian of a give input image with a given sigma.

• Local Maximum Average Distance Of N Closest Neighbors Map Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the maximum distance of touching labels.

• Local Maximum Average Neighbor Distance Map Takes a label map, determines which labels touch, the distance between their centroids and the maximum distancebetween touching neighbors. It then replaces every label with the that value.

• Local Maximum Touching Neighbor Count Map Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local maximum of this count.

• Local Mean Average Distance Of N Closest Neighbors Map Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the mean distance of touching labels.

• Local Mean Average Neighbor Distance Map Takes a label map, determines which labels touch, the distance between their centroids and the mean distancebetween touching neighbors. It then replaces every label with the that value.

• Local Mean Touch Portion Map Takes a label map, determines which labels touch and how much, relatively taking the whole outline of each label into account, and determines for every label with the mean of this value and replaces the label index with that value.

• Local Mean Touching Neighbor Count Map Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local mean of this count.

• Local Median Average Distance Of N Closest Neighbors Map Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the median distance of touching labels.

• Local Median Average Neighbor Distance Map Takes a label map, determines which labels touch, the distance between their centroids and the median distancebetween touching neighbors. It then replaces every label with the that value.

• Local Median Touching Neighbor Count Map Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local median of this count.

• Local Minimum Average Distance Of N Closest Neighbors Map Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the minimum distance of touching labels.

• Local Minimum Average Neighbor Distance Map Takes a label map, determines which labels touch, the distance between their centroids and the minimum distancebetween touching neighbors. It then replaces every label with the that value.

• Local Minimum Touching Neighbor Count Map Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local minimum of this count.

• Local Standard Deviation Average Distance Of N Closest Neighbors Map Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the standard deviation distance of touching labels.

• Local Standard Deviation Average Neighbor Distance Map Takes a label map, determines which labels touch, the distance between their centroids and the standard deviation distancebetween touching neighbors. It then replaces every label with the that value.

• Local Standard Deviation Touching Neighbor Count Map Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local standard deviation of this count.

• Local Threshold Computes a binary image with pixel values 0 and 1 depending on if a pixel value x in image X was above of equal to the pixel value m in mask image M.

• Logarithm Computes base e logarithm of all pixels values.

• Make Isotropic Applies a scaling operation using linear interpolation to generate an image stack with a given isotropic voxel size.

• Mask Label Computes a masked image by applying a label mask to an image.

• Mask Stack With Plane Computes a masked image by applying a binary 2D mask to an image stack.

• Mask Computes a masked image by applying a binary mask to an image.

• Maximum Image And Scalar Computes the maximum of a constant scalar s and each pixel value x in a given image X.

• Maximum Images Computes the maximum of a pair of pixel values x, y from two given images X and Y.

• Maximum Octagon Applies a maximum filter with kernel size 3x3 n times to an image iteratively.

• Maximum X Projection Determines the maximum intensity projection of an image along X.

• Maximum Y Projection Determines the maximum intensity projection of an image along X.

• Maximum Z Projection Bounded Determines the maximum intensity projection of an image along Z within a given z range.

• Maximum Z Projection Determines the maximum intensity projection of an image along Z.

• Maximum2D Box Computes the local maximum of a pixels rectangular neighborhood.

• Maximum2D Sphere Computes the local maximum of a pixels ellipsoidal neighborhood.

• Maximum3D Box Computes the local maximum of a pixels cube neighborhood.

• Maximum3D Sphere Computes the local maximum of a pixels spherical neighborhood.

• Mean X Projection Determines the mean average intensity projection of an image along X.

• Mean Y Projection Determines the mean average intensity projection of an image along Y.

• Mean Z Projection Above Threshold Determines the mean average intensity projection of an image along Z but only for pixels above a given threshold.

• Mean Z Projection Below Threshold Determines the mean average intensity projection of an image along Z but only for pixels below a given threshold.

• Mean Z Projection Bounded Determines the mean average intensity projection of an image along Z within a given z range.

• Mean Z Projection Determines the mean average intensity projection of an image along Z.

• Mean2D Box Computes the local mean average of a pixels rectangular neighborhood.

• Mean2D Sphere Computes the local mean average of a pixels ellipsoidal neighborhood.

• Mean3D Box Computes the local mean average of a pixels cube neighborhood.

• Mean3D Sphere Computes the local mean average of a pixels spherical neighborhood.

• Median Z Projection Determines the median intensity projection of an image stack along Z.

• Median3D Box Computes the local median of a pixels cuboid neighborhood.

• Merge Touching Labels

• Minimum Image And Scalar Computes the minimum of a constant scalar s and each pixel value x in a given image X.

• Minimum Images Computes the minimum of a pair of pixel values x, y from two given images X and Y.

• Minimum Octagon Applies a minimum filter with kernel size 3x3 n times to an image iteratively.

• Minimum X Projection Determines the minimum intensity projection of an image along Y.

• Minimum Y Projection Determines the minimum intensity projection of an image along Y.

• Minimum Z Projection Bounded Determines the minimum intensity projection of an image along Z within a given z range.

• Minimum Z Projection Thresholded Bounded Determines the minimum intensity projection of all pixels in an image above a given threshold along Z within a given z range.

• Minimum Z Projection Determines the minimum intensity projection of an image along Z.

• Minimum2D Box Computes the local minimum of a pixels rectangular neighborhood.

• Minimum2D Sphere Computes the local minimum of a pixels ellipsoidal neighborhood.

• Minimum3D Box Computes the local minimum of a pixels cube neighborhood.

• Minimum3D Sphere Computes the local minimum of a pixels spherical neighborhood.

• Multiply Image And Scalar Multiplies all pixels value x in a given image X with a constant scalar s.

• Multiply Images Multiplies all pairs of pixel values x and y from two image X and Y.

• Multiply Stack With Plane Multiplies all pairs of pixel values x and y from an image stack X and a 2D image Y.

• Non Local Means Applies a non-local means filter using a box neighborhood with a Gaussian weight specified with sigma to the input image.

• Not Equal Constant Determines if two images A and B equal pixel wise.

• Not Equal Determines if two images A and B equal pixel wise.

• Opening Box Apply a binary opening to the input image by calling n erosions and n dilations subsequenntly.

• Parametric Watershed Apply a binary watershed to a binary image and introduce black pixels between objects.

• Power Images Calculates x to the power of y pixel wise of two images X and Y.

• Power Computes all pixels value x to the power of a given exponent a.

• Pull To ROIManager Pulls a binary image from the GPU memory and puts it in the ROI Manager.

• Reduce Labels To Labelled Spots Takes a label map and reduces all labels to their center spots. Label IDs stay and background will be zero.

• Reduce Stack Reduces the number of slices in a stack by a given factor. With the offset you have control which slices stay:

• With factor 3 and offset 0, slices 0, 3, 6,... are kept. * With factor 4 and offset 1, slices 1, 5, 9,... are kept.

• Replace Pixels If Zero Replaces pixel values x with y in case x is zero.

• Reslice Bottom Flippes Y and Z axis of an image stack. This operation is similar to ImageJs 'Reslice [/]' method but offers less flexibility such as interpolation.

• Reslice Left Flippes X, Y and Z axis of an image stack. This operation is similar to ImageJs 'Reslice [/]' method but offers less flexibility such as interpolation.

• Reslice Right Flippes X, Y and Z axis of an image stack. This operation is similar to ImageJs 'Reslice [/]' method but offers less flexibility such as interpolation.

• Reslice Top Flippes Y and Z axis of an image stack. This operation is similar to ImageJs 'Reslice [/]' method but offers less flexibility such as interpolation.

• Rigid Transform Applies a rigid transform using linear interpolation to an image stack.

• Rotate Clockwise Rotates a given input image by 90 degrees clockwise.

• Rotate Counter Clockwise Rotates a given input image by 90 degrees counter-clockwise.

• Rotate2D Rotates an image in plane.

• Rotate3D Rotates an image stack in 3D.

• Smaller Constant Determines if two images A and B smaller pixel wise.

• Smaller Or Equal Constant Determines if two images A and B smaller or equal pixel wise.

• Smaller Or Equal Determines if two images A and B smaller or equal pixel wise.

• Smaller Determines if two images A and B smaller pixel wise.

• Sobel Slice By Slice Convolve the image with the Sobel kernel slice by slice.

• Sobel Convolve the image with the Sobel kernel.

• Sphere Transform Turns an image stack in XYZ cartesian coordinate system to an AID polar coordinate system.

• Squared Difference Determines the squared difference pixel by pixel between two images.

• Standard Deviation Box Computes the local standard deviation of a pixels box neighborhood.

• Standard Deviation Sphere Computes the local standard deviation of a pixels spherical neighborhood.

• Standard Deviation Z Projection Determines the standard deviation intensity projection of an image stack along Z.

• Subtract Gaussian Background Applies Gaussian blur to the input image and subtracts the result from the original image.

• Subtract Image From Scalar Subtracts one image X from a scalar s pixel wise.

• Subtract Images Subtracts one image X from another image Y pixel wise.

• Sum X Projection Determines the sum intensity projection of an image along Z.

• Sum Y Projection Determines the sum intensity projection of an image along Z.

• Sum Z Projection Determines the sum intensity projection of an image along Z.

• Tenengrad Slice By Slice Convolve the image with the Tenengrad kernel slice by slice.

• Tenengrad Convolve the image with the Tenengrad kernel slice by slice.

• Threshold Default 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.

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

• Threshold Huang 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.

• Threshold IJ Iso Data 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.

• Threshold Intermodes 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.

• Threshold Iso Data 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.

• Threshold Li 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.

• Threshold Max Entropy 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.

• Threshold Mean 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.

• Threshold Min Error 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.

• Threshold Minimum 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.

• Threshold Moments 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.

• Threshold Otsu 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.

• Threshold Percentile 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.

• Threshold Renyi Entropy 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.

• Threshold Shanbhag 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.

• Threshold Triangle 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.

• Threshold Yen 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.

• Top Hat Box Applies a top-hat filter for background subtraction to the input image.

• Top Hat Sphere Applies a top-hat filter for background subtraction to the input image.

• Touching Neighbor Count Map Takes a label map, determines which labels touch and replaces every label with the number of touching neighboring labels.

• Translate2D Translate an image stack in X and Y.

• Translate3D Translate an image stack in X, Y and Z.

• Transpose XY Transpose X and Y axes of an image.

• Transpose XZ Transpose X and Z axes of an image.

• Transpose YZ Transpose Y and Z axes of an image.

• Undefined To Zero Copies all pixels instead those which are not a number (NaN) or infinity (inf), which are replaced by 0.

• Variance Box Computes the local variance of a pixels box neighborhood.

• Variance Sphere Computes the local variance of a pixels spherical neighborhood.

• Voronoi Labeling Takes a binary image, labels connected components and dilates the regions using a octagon shape until they touch.

• Voronoi Octagon Takes a binary image and dilates the regions using a octagon shape until they touch.

• Weka Label Classifier Applies a pre-trained CLIJx-Weka model to an image and a corresponding label map.

• Within Intensity Range Generates a binary image where pixels with intensity within the given range are 1 and others are 0.

• Z Position Of Maximum Z Projection Determines a Z-position of the maximum intensity along Z and writes it into the resulting image.

• Z Position Projection Project a defined Z-slice of a 3D stack into a 2D image.

• Z Position Range Projection Project multiple Z-slices of a 3D stack into a new 3D stack.

• Zoom See Scale2D and Scale3D.

249 operations listed.

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