Abstract
Autofluorescence is a long-standing problem that has hindered fluorescence microscopy image analysis. To address this, we have developed a method that identifies and removes autofluorescent signals from multi-channel images post acquisition. We demonstrate the broad utility of this algorithm in accurately assessing protein expression in situ through the removal of interfering autofluorescent signals.
Availability and implementation https://ellispatrick.github.io/AFremover
Contact ellis.patrick{at}sydney.edu.au
Supplementary information Supplementary Figs. 1–13
Copyright
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