Processing of series of 2D images in a 3D fashion (out-of-core)
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## Processing of series of 2D images in a 3D fashion (out-of-core)

The programs in this section are dedicated to processing series of 2D images in a 3D fashion out-of-core. This is intended for large images that would not fit into the main memory if processing was to be done as a true 3D images. As a result, only spacial, non-iterative operators are supported.

mia-2dimagestack-cmeans

This program first evaluates a sparse histogram of an input image series, then runs a c-means classification over the histogram and then writes the probability mapping for thr original intensity values

mia-2dstack-cmeans-presegment

This program first evaluates a sparse histogram of an input image series, then runs a c-means classification over the histogram, and then estimates the mask for one (given) class based on class probabilities. This program accepts only images of eight or 16 bit integer pixels.

mia-2dstackfilter

This program is used to filter and convert a series of 2D gray scale images in a 3D fashion by running filters (filter/2dimage) as given on the command line.

mia-3ddistance

This program takes two binary masks as input and evaluates the distance of one mask with respect to the other in voxel space. The output is given as text file with the coordinates of the source voxels and their distance to the reference mask. Correction for voxel size must be done after processing.

mia-multihist

This program evaluates the histogram over a series of 2D images

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