PerfectlyAverage: A classical open‐source software method to determine the optimal averaging parameters in laser scanning fluorescence microscopy

Laser scanning fluorescence microscopy (LSFM) is a widely used imaging method, but image quality is often degraded by noise. Averaging techniques can enhance the signal-to-noise ratio (SNR), but while this can improve image quality, excessive frame accumulation can introduce photobleaching and may lead to unnecessarily long acquisition times. A classical software method called PerfectlyAverage is presented to determine the optimal number of frames for averaging in LSFM using SNR, photobleaching, and power spectral density (PSD) measurements. By assessing temporal intensity variations across frames in a time series, PerfectlyAverage identifies the point where additional averaging ceases to provide significant noise reduction. Experiments with fluorescently stained tissue paper and fibroblast cells validated the approach, demonstrating that up to a fourfold reduction in averaging time may be possible. PerfectlyAverage is open source, compatible with any LSFM data, and it is aimed at improving imaging workflows while reducing the reliance on subjective criteria for choosing the number of averages.