Table of Contents
In the following chapter, we will list a number of typical modules for typical questions, with brief information on their main purposes.
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To learn about module details, read the module help and have a look at the example network. |
ImageLoad: opens an image file stored in one of the following formats: DICOM, TIFF, DICOM/TIFF, RAW, LUMISYS, PNM, Analyze, PNG, JPEG.
LocalImage: works like ImageLoad, but loads images relative to the network or the local MeVisLab installation.
ImageSave: saves an image to file using one of the following image file formats: DICOM, TIFF, DICOM/TIFF, RAW, LUMISYS, PNM, Analyze, PNG, JPEG.
Info: shows information about the currently connected input image, like image size, page size, voxel size, total volume, world matrix, etc.
MinMaxScan: scans the input and updates the minimum and maximum values of the output image. The data type can be be adapted, left unchanged or set to an arbitrary one.
ImagePropertyConvert: allows to freely change page size, minimum or maximum value, data type, or world matrix of an image.
ImageStatistics: computes some statistics of the input image voxels (subset of voxels).
SubImage: extracts subimages from an input image based on either voxel start/size, voxel start/end or world start/end. Can also be used to create a region larger than the input image.
Resample3D: resamples an image in 3D on an arbitrary planar parallel grid. 17 filters are available.
Reformat: can be used to reformat an image to a reference image, or to create reformatted overlays via SoView2D
/SoOrthoView2D
.
Scale: scales the input image to another interval. The source and target scale interval can be defined.
Arithmetic1: performs arithmetic operations on one image. For example, in case of Add
, the constant value is added to each voxel of the input image.
Arithmetic2: performs arithmetic operations on two images. For example, in case of Add
, the values of input image 2 are added to each voxel of input image 1.
Switch: selects one of up to 25 input images depending on an input parameter. The selected image is passed unchanged to the output.
Mask: masks the image of input 1 with the mask at input 2. For example, in case of Masked Original
(default), all pixels from the first input are passed unchanged to the output if non-zero values are found at their positions in the second input image. Otherwise background values are passed to the output.
TestPattern: generates a test image of a defined size, page size, data type and pattern (stripes, checkers, ramps, etc.).
AddNoise: produces noise based on a scalar input image and a chosen distribution, for example uniform noise, Gaussian noise, Salt&Pepper, etc.
Convolution: offers standard kernel-based filters like Average, Gauss, Laplace or Sobel.
ExtendedConvolution: offers standard convolution filters similar to Convolution
but with more flexible kernel sizes and kernel geometry.
Rank: offers rank-based kernel filters like Min, Max, Median, Rank or Index.
Morphology: implements dilation and erosion filters. By using threshold intervals, filtering can be applied selectively to regions in the image.
CalculateGradient: computes the slope of image value changes in regions around each voxel in an image.
Threshold: transforms the input image into a binary image, in which voxels below the threshold are set to the image minimum value, and voxels at or above the threshold are set to the image maximum value. Can be used with a relative threshold.
IntervalThreshold: processes an image by filtering just those image values that lie in a certain gray value interval. Voxels outside this range can be set to zero or to a user-defined fill value. This can be useful for the segmentation of objects that are expected to have gray values in a defined interval.
RegionGrowing: provides a simple threshold/interval-based 1D/2D/3D/4D region growing algorithm. A threshold/interval and at least one seed are necessary as start parameters.
RegionGrowingMacro: extends the options of RegionGrowing
by adding a viewer (View2D
) and a marker editor to simplify its usage.
ComputeConnectedComponents: performs a connected component analysis on 2D / 3D grayscale images. You need other modules mentioned in the seeAlso of the module to process its output.
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