Friedrich-Alexander-Universität Erlangen-Nürnberg

Advanced fundus imaging for early detection of eye diseases

Advanced fundus imaging for early detection of eye diseases

The long-term goal of this research is to facilitate the early detection of eye diseases, especially glaucoma, and to analyze their progress based on new imaging techniques. An important measure for diagnosing glaucoma is the spatial distribution of the thickness of the retinal nerve fibre layer (RNFL), which can be measured using frequency domain optical coherent tomography (OCT).

We propose a novel retinal nerve fibre layer segmentation algorithm for frequency domain data that can be applied on scans from both normal healthy subjects, as well as glaucoma patients, using the same set of parameters. In addition, the algorithm remains almost unaffected by image quality. The main part of the segmentation process is based on the minimization of an energy function consisting of gradient and local smoothing terms.

The mean absolute segmentation error over all A-Scans lies below 10 μm on 95.1% of the images. Thus our approach provides a reliable tool for extracting diagnostic relevant parameters from OCT B-Scans for glaucoma diagnosis.

Automated measurements of the retinal nerve fibre layer thickness on circular OCT B-scans will be useful for automated diagnosis assistance tools in future projects and can provide physicians additional parameters for glaucoma diagnosis.

The developed software OCTSEG is available at

Fig. 1. Example results. Automatically segmented retinal nerve fiber layer thickness. (a) normal eye. (b) and (c) glaucomatous eyes. (d) normal eye, very low image quality. White arrows indicate segmentation errors. For details see (Mayer, Hornegger et al. 2010). Copyright OSA.

Mayer, M. A., J. Hornegger, C. Y. Mardin, R. P. Tornow (2010). "Retinal Nerve Fiber Layer Segmentation on FD-OCT Scans of Normal Subjects and Glaucoma Patients." Biomed. Opt. Express 1(5): 1358-1383.


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Optical Metrology
Optical Material Processing
Optics in Medicine
Optics in Communication and Information Technology
Optical Materials and Systems
and Computational Optics.