I'm reading an article (full text here) that analyze the dynamics of localization of a GFP-tagged transcription factor (Crz1) over the time at the single-cell level, by taking movies in a fluorescent microscope.
In Methods section they say:
Fluorescence cell images were segmented using a Hough transformation algorithm in Matlab, provided by Sharad Ramanathan. Localization score was determined by the difference between the mean intensity of the 5 brightest pixels in the cell and mean intensity of the rest of the pixels in the cell.
The segmentation process here seems to be the identification of cells over the background. They then calculate a localization score, for each frame of the video, for every cell. Now there's the part that I can't understand:
Bursts were identified by thresholding traces at >1 standard deviations above background noise, estimated from the lowest 20% of values.
I searched some definitions of "background noise", but I can't figure out what does it mean in this particular context. Moreover, "lowest 20% of values" of what?
Is it plausible that they define it for the lowest 20% of values of localization scores over the time, at the cell each time considered?
Maybe can be useful a screenshot of a single cell in a photogram of the video: