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Dept. of Computer Sc. » Pattern Recognition » Our Team » Mayer, Markus » Automated Retinal Layer Segmentation
Dipl.-Inf. Markus MayerAlumnus of the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-NürnbergThe vision of my work is to develop image processing methods that provide new tools for ophthalmologists to ease the detection of glaucoma and related eye diseases. Automated Retinal Layer SegmentationOCT allows a direct visualization of the retinal background and its layered structure. This proved to be of substantial benefit for the glaucoma disease research. During glaucoma progression the supporting tissue and nerve fibers in the retina are lost. Thus a thinning of the retinas innermost layer, the retinal nerve fiber layer (RNFL) is observed. Since the first appearance of commercially available OCT systems automated retinal layer segmentation algorithms were presented to objectively quantify this thickness loss. We develop a retinal layer segmentation algorithm with the following goals:
Current State:Currently published journal articles:
Early versions of a segmentation algorithm for circular OCT scans based on fuzzy C-means clustering were published:
For this project, the OCTSEG Software for segmenting and visualizing OCT data was written. This software is downloadable and may be used for free. |