CellProfiler Analyst 3.0: Accessible data exploration and machine learning for image analysis

TL;DR

CellProfiler Analyst 3.0 is an improved, open-source tool that enhances image data exploration and machine learning capabilities, including neural networks and better integration with CellProfiler 4.

Contribution

Introduction of CellProfiler Analyst 3.0 with neural network support, rare object identification, and improved interoperability for advanced image data analysis.

Findings

Supports neural network classifiers for image data

Enables identification of rare object subsets

Improves integration with CellProfiler 4

Abstract

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.