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C. M. Novalis, D. A. Orlock, J. Slakter, J. Klancnik, D. C. Ferrara, R. E. Curtin, L. A. Yanuzzi; Fundus Autofluorescence (FAF) Mean Imaging Using a Fundus Camera Based System. Invest. Ophthalmol. Vis. Sci. 2008;49(13):4211.
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© ARVO (1962-2015); The Authors (2016-present)
To investigate the use of mean imaging software applications to perform Fundus Autofluorescence (FAF) imaging in order to enhance the image quality on a fundus based camera system.
Twenty eyes of 12 patients with macular disease patterns were imaged for Fundus Autofluorescence (FAF) patterns using a Topcon 50 IX fundus camera equipped with autofluorescent filters (580 nm excitation and 695 nm barrier filters), digital camera (Kodak Megaplus 1.4i) and ImageNet software (Topcon Corporation, Tokyo, Japan). Three images were taken of each eye and processed using prototype mean averaging software. The software performed alignment and noise reducing algorithms. The images taken on the FAF system were centered and focused on the macula and other posterior pole pathology.Single FAF images taken with a fundus camera or with a HRA 2 (Heidelberg Engineering Heidelberg Germany) demonstrate poor signal to noise ratio (SNR) and low contrast. By averaging multiple images, the HRA2 mean averaging software produces images with increased contrast, which consequently enhance the feasibility of FAF imaging in clinical settings. We are investigating a similar software application using a fundus based camera system, to increase the contrast of FAF imaging.
The mean enhanced and single unenhanced images were compared by the authors for image quality and clinical diagnostic value. The mean software produce images with higher contrast and less noise which increased the clinical diagnostic value when compares to unenhanced images. It was also possible to better image patients with media opacities. Prior to this technique FAF imaging was limited by the severity of the opacities.
Using mean averaging software improves the image quality of fundus camera based fundus autofluorescence imaging. Fundus autofluorescence imaging using mean averaging software is expected to play an important role in the evaluation of retinal pathology in both investigational as well as clinical practice settings.
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