Foylan S, Rooney L M, Amos W B, Gould G W, McConnell G
Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK.
MRC Laboratory of Molecular Biology, Cambridge, UK.
J Microsc. 2025 Aug;299(2):155-165. doi: 10.1111/jmi.13425. Epub 2025 May 14.
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.
激光扫描荧光显微镜（LSFM）是一种广泛使用的成像方法，但图像质量常常会因噪声而下降。平均技术可以提高信噪比（SNR），虽然这可以改善图像质量，但过度的帧累积会导致光漂白，并可能导致不必要的长时间采集。本文提出了一种名为PerfectlyAverage的经典软件方法，用于通过信噪比、光漂白和功率谱密度（PSD）测量来确定LSFM中平均所需的最佳帧数。通过评估时间序列中各帧的时间强度变化，PerfectlyAverage可以确定额外平均不再能显著降低噪声的点。对荧光染色的薄纸和成纤维细胞进行的实验验证了该方法，表明平均时间最多可减少四倍。PerfectlyAverage是开源的，与任何LSFM数据兼容，旨在改善成像工作流程，同时减少对选择平均次数的主观标准的依赖。
