![]() The plugin does not require any programming skill and can analyze cells in many different acquisition setups. Once the analysis is set up, it can be automatically and efficiently performed on many images. This procedure may be applied in batch mode to multiple microscopy files. Our software provides a modular and flexible strategy to perform cell classification through a wizard-like graphical user interface in which the user is intuitively guided through each step of the analysis. Our workflow consists of (a) image preprocessing actions, data spatial calibration, and region of interest for analysis (b) segmentation to isolate cells from background (optionally including user-defined preprocessing steps helping the identification of cells) (c) extraction of features from each cell (d) filters to select relevant cells (e) definition of specific criteria to be included in the different cell types (f) cell classification and (g) flexible analysis of the results. It consists of an open-source plugin for Fiji or ImageJ to detect and classify cells in 2D images. We describe a semiautomated and versatile tool called Cell-TypeAnalyzer to avoid the time-consuming and biased manual classification of cells according to cell types. Fluorescence microscopy techniques have experienced a substantial increase in the visualization and analysis of many biological processes in life science. ![]()
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