Robin Hood: non-fitting, non-smoothing image detrending for bleaching correction
Nolan, R.; Iliopoulou, M.; Siebold, C.; Jones, E. Y.; Padilla-Parra, S.
Show abstract
Recent advances in protein labelling--gene tagging with CRIPSR-Cas9--have made it possible to label proteins of interest endogenously. This represents a major breakthrough in the field of quantitative microscopy, especially when quantifying protein-protein interactions. This is because over-expression of labelled proteins may cause a distortion in localization, function and perhaps artificially force protein-protein interactions due to crowding effects. A microscopy technique that is particularly well suited to detect protein interactions with low photon budgets is number and brightness (N&B). Detrending (removal of global trends in data) is a necessary pre-processing step to N&B calculations, but all current detrending methods perform poorly at low intensities. Here, we present the Robin Hood automatic detrending algorithm which performs well at low intensities, evaluating it with simulated and low photon budget live cell images. RH is available as an ImageJ plugin and as an R package.\n\nSTATEMENT OF SIGNIFICANCEFluorescence microscopy in general and Fluorescence fluctuation methods in particular are very much dependent on detrend algorithms and so far, the user needs to decide an arbitrary number to correct for bleaching when using the box plot or the running average approach. Here, we have developed a tool available to everybody as an ImageJ plugin that is automatic, user-free and able to correct bleached images with very low photon counts.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- ColiCoords: A Python package for the analysis of bacterial fluorescence microscopy data 93%
- Determining the Statistical Significance of the Difference Between Arbitrary Curves: A Spreadsheet Method 93%
- Mitochondrial event localiser (MEL) to quantitatively describe fission, fusion and depolarisation in the three-dimensional space 93%
Similar papers in this journal
Similar papers in this journal
- ERICA: Emulated Retinal Image CApture - A tool for testing, training and validating retinal image processing methods 93%
- FluoSim: simulator of single molecule dynamics for fluorescence live-cell and super-resolution imaging of membrane proteins 93%
- Stimulated emission depletion microscopy with a single depletion laser using five fluorochromes and fluorescence lifetime phasor separation 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.