Astrocytes are non-neural cells, restricted to the brain and spinal cord, whose functions and morphology depend on their location. Astrocyte-astrocyte and astrocyte-neuron interactions occur through cytoplasmic Ca2+ levels changes, that are assessed to determine cell function and response (i.e. drug testing). Evaluation of changes in intracellular Ca2+ levels is mostly centered on fluorescence imaging approaches, performed through video recording of cells incubated with Ca2+-sensitive dyes. By observing ion concentration shifts over time in a delimited region of interest (ROI) comprising a single cell, it is possible to attain conclusions on cell responses to specific stimuli. Our work describes a tool named SIGAA – SIGnaling Automated Analysis, for astrocyte ROI-based fluorescent imaging, which is tailored for two wavelengths dyes by using two inputs of Ca2+ signaling recorded frames/videos and outputs a set of features relevant to the experiment’s conclusions and cell characterization. SIGAA performs automatic drift correction for the two recorded videos with a template matching algorithm, followed by astrocyte identification (ROI) using morphological reconstruction techniques. SIGAA then extracts intracellular Ca2+ evolution functions for all identified ROIs, detects function transients, and estimates a set of features for each signal, which are very similar to the ones obtained by the traditional methods and software used so far. SIGAA is a new fully automated tool, which can speed up hour-long studies and analysis to a few minutes, showing reliable results as the validity tests indicate.