Cell classification

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.

A workflow combining ImageJ macro and manually using Trainable Weka Segmentation plugin for counting clumped cells.

An ImageJ plugin (author: Kurt De Vos) for counting multiple cell classes manually, which overlays already-counted cells on the image. It is controlled via its own graphical user interface, and can export and load results.

This module classifies objects into a number of different bins according to the value of a measurement (e.g., by size, intensity, shape). It reports how many objects fall into each class as well as the percentage of objects that fall into each class. The module asks you to select the measurement feature to be used to classify your objects and specify the bins to use. It also requires you to have run a measurement or CalculateMath previous to this module in the pipeline so that the measurement values can be used to classify the objects.