Genetically Encoded Voltage Indicators (GEVIs) are tools to directly measure membrane voltages in cells through fluorescence. Spiking HEK cells, cells which can produce easily evocable voltage spikes, are useful in studying GEVIs. Populations of spiking HEK cells expressing GEVI variants can be used to identify the best GEVI variants in the population in terms of speed and sensitivity. To facilitate such screenings an automated image analysis pipeline is developed in this project. The pipeline corrects for motion artifacts, segments the single spiking HEK cell with an IoU of 0.881 compared to manual annotation and, extracts sensitivity, speed and membrane localization of the GEVIs expressed by these
cells. When comparing sensitivity, speed and, membrane localization values extracted by the pipeline to manually calculated ground truth values, an error of 10.672%, 16.639% and, 13.107% is calculated in the averages of sensitivity, speed and, membrane localization, respectively. To demonstrate its functionality, the pipeline screens a population of spiking HEK cells expressing GEVI variants. From this screening, the pipeline identifies a single best GEVI variant with a sensitivity of 415.2% and a speed of 131.7/seconds.