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 implementationhttps://ellispatrick.github.io/AFremover Contactellis.patrick@sydney.edu.au Supplementary informationSupplementary Figs. 1-13