modules/ilastik_multicut

Ilastik is a tool that utilizes machine learning algorithms to classify pixels, segment, track and count cells in images. Ilastik contains a graphical user interface to interactively label pixels. However, this nextflow module will implement the —headless mode, to apply pixel classification using a pre-trained .ilp file on an input image.

multicutsegmentationpixel classification

https://github.com/nf-core/modules/[...]/modules/nf-core/ilastik/multicut

Description

Input

name:type

description

pattern

`meta:map`

Groovy Map containing sample information e.g. [ id:‘test’ ]

`h5:file`

h5 file containing image stack to classify file

*.{h5,hdf5}

`probs:file`

Probability map for boundary based segmentation as exported by the pixel classification workflow.

*.{h5,hdf5}

`ilp:file`

Trained ‘Boundary-based Segmentation with Multicut’ .ilp project file

*.{ilp}

Output

name:type

description

pattern

`mask`

`meta:map`

Groovy Map containing sample information e.g. [ id:‘test’, single_end:false ]

`*.tiff:file`

Multicut segmentation mask output.

*.{tiff}

`versions`

`versions.yml:file`

File containing software versions

versions.yml

Tools

ilastik

Ilastik is a user friendly tool that enables pixel classification, segmentation and analysis.

ilastik.org ilastik.org/documentation https://github.com/ilastik/ilastik