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Zhengyu Pang: Quantitative fluorescence image analysis using ImageJ


Obtaining a fluorescence image is a simple snap but involving a complex process from generating fluorescence, optics, analog to digital conversion with a CCD camera. Many signal and image processing steps are involved in the final digital image. In this talk, mechanisms of the epifluorescence and CCD camera are reviewed to get better understanding of a fluorescence image, followed by demonstration of image pre-processing (illumination pattern correction), autofluorescence removal, and co-localization of biomarkers using ImageJ and its plugin, JACoP (Just Another Colocalization Program).

Due to the limitation of the optics, the illumination is not uniform across field of view and has to be corrected. ImageJ divide operation is used for correcting uneven illumination but has to consider the contribution from dark pixel intensity set by the camera. Endogenous autofluorescence is always compound with specific signals from fluorescence dyes and has to be removed before quantification. Image calculation/Image subtraction is employed to remove autofluorescence (pre-stain image) from post stain image that contains both autofluorescence and specific fluorescence. The successful autofluorescence removal requires two conditions: 1) Pre-stain and post-stain images are registered to each other (in other words, they are aligned); 2) same exposure time is used for both images. In the case of different exposure, images needs be scaled before subtraction. Alternatively a customized filter set is used to acquire pure autofluorescence. By comparing images acquired by standard filter set and customized filter set with an autofluorescence only sample, autofluorescence contribution can be determined and subsequently subtracted. Finally co-localization of three cytokeratins was demonstrated in a breast cancer tissue sample.


quantitative, autofluorescence removal, illumination pattern correction, co-localization

Administrative data

Presenting author: Zhengyu Pang
Organisation: General Electric Company Global Research Center


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