Image classification

Image clustering

A software toolkit for computational morphometry of biomedical images, CMTK comprises a set of command line tools and a back-end general-purpose library for processing and I/O.

The command line tools primarily provide the following functionality: registration (affine and nonrigid; single and multi-channel; pairwise and groupwise), image correction (MR bias field estimation; interleaved image artifact correction; EPI unwarping), processing (filters; combination of segmentations via voting and STAPLE; shape-based averaging), statistics (t-tests; general linear model).


Advanced Cell Classifier is a data analyzer program to evaluate cell-based high-content screens and tissue section images developed at the Biological Research Centre, Szeged and FIMM, Helsinki (formerly at ETH Zurich). The basic aim is to provide a very accurate analysis with minimal user interaction using advanced machine learning methods.

Advanced Cell Classifier

This is the "prediction step" of the Pyxit segmentation model builder. It is a learnable segmentation algorithm based on ground-truth images and segmentation mask. It learns a multiple output pixel classification algorithm. It downloads from Cytomine-Core annotation images+alphamasks from project(s), build a segmentation (pixel classifier) model which is saved locally. Typical application: tumor detection in tissues in histology slides. 

Pyxit example

Import ROI from a zip file produced with ImageJ's ROI manager. Works as a standalone plugin and as a block for Protocols

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