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The texture analysis of the retinal nerve fiber layer (RNFL) in colour fundus images is a promising tool for early glau-coma diagnosis. This paper describes model-based method for detection of changes in the RNFL. The method utilizes Gaussian Markov random fields (GMRF) and the least-square error (LSE) estimate for the local RNFL texture modelling. The(More)
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 2D directional matched filtering, enables to remove areas occluded by blood vessels thus leaving remaining retinal area available to the(More)
A method for correction of non-uniform illumination in colour fundus images based on the B-spline approximation of the illumination surface is presented. The control points for B-splines are determined from an original image, separately from the red, green and blue channel. The estimated illumination surface is used in a multiplicative model for fast(More)
Images of ocular fundus are routinely utilized in ophthalmology. Since an examination using fundus camera is relatively fast and cheap procedure, it can be used as a proper diagnostic tool for screening of retinal diseases such as the glaucoma. One of the glaucoma symptoms is progressive atrophy of the retinal nerve fiber layer (RNFL) resulting in(More)
The paper presents an overview of image analysis activities of the Brno DAR group in the medical application area of retinal imaging. Particularly, illumination correction and SNR enhancement by registered averaging as preprocessing steps are briefly described; further mono-and multimodal registration methods developed for specific types of(More)
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