Journal
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
Volume 36, Issue 6, Pages 431-441Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2012.04.006
Keywords
Retinal imaging; Fundus-camera; Retinal vessel tree; Retinal neural fibre layer; Image segmentation; 20 matched filtering; Texture analysis; 2D spectra; Edge maps
Funding
- research centre DAR by the Ministry of Education, Czech Republic [1M0572]
- Ministry of Education, Czech Republic [MS 0021630513]
- bilateral German-Czech grant [D10-CZ16/09-10]
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An automatic method of segmenting the retinal vessel tree and estimating status of retinal neural fibre layer (NFL) from high resolution fundus camera images is presented. First, reliable blood vessel segmentation, using 20 directional matched filtering, enables to remove areas occluded by blood vessels thus leaving remaining retinal area available to the following NFL detection. The local existence of rather faint and hardly visible NFL is detected by combining several newly designed local textural features, sensitive to subtle NFL characteristics, into feature vectors submitted to a trained neural-network classifier. Obtained binary retinal maps of NFL distribution show a good agreement with both medical expert evaluations and quantitative results obtained by optical coherence tomography. (C) 2012 Elsevier Ltd. All rights reserved.
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