Object Classification using ilastik

Type
Author
ilastik team
Requires
Execution Platform
Programming Language
Supported image dimension
Interaction Level
License/Openness
Description

This workflow classifies objects based on object-level features (e.g. intensity based, morphology based, etc) and user annotations. It needs segmentation images besides the raw image data. Segmentation images can be obtained from ilastik pixel classification, or binary segmentation images from other tools. Within the object classification, one can prefilter objects through thresholds (on pixel probability image) or object sizes (on segmentation image). Outputs are predicted classification label images. Selected features can also be exported. Advanced users also have possibilities to add customized (object) features for classification in a simple plugin fashion through python scripts.

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Entry Curator
Last modified
05/16/2018 - 02:00