  Image-based experiments can yield many thousands of individual measurements
describing each object of interest, such as cells in microscopy screens.
CellProfiler Analyst is a free, open-source software package designed for the
exploration of quantitative image-derived data and the training of machine
learning classifiers with an intuitive user interface. We have now released
CellProfiler Analyst 3.0, which in addition to enhanced performance adds
support for neural network classifiers, identifying rare object subsets, and
direct transfer of objects of interest from visualisation tools into the
Classifier tool for use as training data. This release also increases
interoperability with the recently released CellProfiler 4, making it easier
for users to detect and measure particular classes of objects in their
analyses.
