The Role of Retinal Vascular Density as a Screening Tool for Ageing and Stroke.

OBJECTIVES: To measure the density of retinal vessels from digitized fundus photographs in patients with recent stroke and age-matched controls. To investigate whether the parameter retinal vascular density (RVD) served as a quantitative marker for cerebrovascular events. METHODS: Digitized fundus photographs of n = 158 subjects with stroke or transient ischemic attack within 1 year at the time of examination and n = 1,250 age-matched controls without any remarkable medical history were examined. Sex, hypertension, and diabetes were considered to be cofactors. Measurement of RVD was performed with a computer-aided image-analyzing program by segmenting automatically all visible retinal vessels and measuring areas of vessels in distinct circles around the optic disk. RESULTS: In controls RVD dwindles with increasing distance from the optic disk. RVD decreased significantly with age (p = 0.000). Stroke patients showed significantly lower values of RVD of -15% in comparison to age-matched controls. In old subjects, stroke in combination with hypertension is associated with a significant decreased RVD, and in middle-aged subjects diabetes and stroke are associated with a significant decreased RVD (p = 0.01). CONCLUSION: Age and stroke are significant risk factors for decreased RVD. Diabetes and arterial hypertension are additional significant risk factors in patients with stroke with respect to RVD.

Quantitative 3D-OCT motion correction with tilt and illumination correction, robust similarity measure and regularization.

Variability in illumination, signal quality, tilt and the amount of motion pose challenges for post-processing based 3D-OCT motion correction algorithms. We present an advanced 3D-OCT motion correction algorithm using image registration and orthogonal raster scan patterns aimed at addressing these challenges. An intensity similarity measure using the pseudo Huber norm and a regularization scheme based on a pseudo L0.5 norm are introduced. A two-stage registration approach was developed. In the first stage, only axial motion and axial tilt are coarsely corrected. This result is then used as the starting point for a second stage full optimization. In preprocessing, a bias field estimation based approach to correct illumination differences in the input volumes is employed. Quantitative evaluation was performed using a large set of data acquired from 73 healthy and glaucomatous eyes using SD-OCT systems. OCT volumes of both the optic nerve head and the macula region acquired with three independent orthogonal volume pairs for each location were used to assess reproducibility. The advanced motion correction algorithm using the techniques presented in this paper was compared to a basic algorithm corresponding to an earlier version and to performing no motion correction. Errors in segmentation-based measures such as layer positions, retinal and nerve fiber thickness, as well as the blood vessel pattern were evaluated. The quantitative results consistently show that reproducibility is improved considerably by using the advanced algorithm, which also significantly outperforms the basic algorithm. The mean of the mean absolute retinal thickness difference over all data was 9.9 um without motion correction, 7.1 um using the basic algorithm and 5.0 um using the advanced algorithm. Similarly, the blood vessel likelihood map error is reduced to 69% of the uncorrected error for the basic and to 47% of the uncorrected error for the advanced algorithm. These results demonstrate that our advanced motion correction algorithm has the potential to improve the reliability of quantitative measurements derived from 3D-OCT data substantially.

Thickness related textural properties of retinal nerve fiber layer in color fundus images.

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 variations of the RNFL thickness. Here, we introduce a novel approach to capture these variations using computer-aided analysis of the RNFL textural appearance in standard and easily available color fundus images. The proposed method uses the features based on Gaussian Markov random fields and local binary patterns, together with various regression models for prediction of the RNFL thickness. The approach allows description of the changes in RNFL texture, directly reflecting variations in the RNFL thickness. Evaluation of the method is carried out on 16 normal ("healthy") and 8 glaucomatous eyes. We achieved significant correlation (normals: ρ=0.72±0.14; p≪0.05, glaucomatous: ρ=0.58±0.10; p≪0.05) between values of the model predicted output and the RNFL thickness measured by optical coherence tomography, which is currently regarded as a standard glaucoma assessment device. The evaluation thus revealed good applicability of the proposed approach to measure possible RNFL thinning.