Achieving cellular resolution for in vivo retinal images of transgenic GFAP-GFP mice via image processing

In vivo retinal images of transgenic mice, expressing GFP under the control of the GFAP (glial fibrillary acidic protein) promoter, have very poor signal-to-noise ratio (SNR) and cellular resolution such that the analysis of GFAP-GFP expressing retinal cells from these images can be a very challenging task. We report an image averaging method based on a pixel rank matching criterion which significantly enhances both these image attributes. We also show that it compares favorably against direct image averaging and a commercial averaging routine available from the Heidelberg Retinal Angiograph 2 software.