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.
Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, The Nanos, 04-01, Singapore. skumar@ibn.a-star.edu.sg
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D000818:Animals; D020869:Gene Expression Profiling; D005904:Glial Fibrillary Acidic Protein; D049452:Green Fluorescent Proteins / Q000235:genetics; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D051379:Mice; D008822:Mice, Transgenic; D009419:Nerve Tissue Proteins / Q000378:metabolism*; D012160:Retina / Q000166:cytology* / Q000378:metabolism*; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity
D005904:Glial Fibrillary Acidic Protein; D009419:Nerve Tissue Proteins; C528900:glial fibrillary astrocytic protein, mouse; D049452:Green Fluorescent Proteins