132 research outputs found

    Novel non-contact retina camera for the rat and its application to dynamic retinal vessel analysis

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    We present a novel non-invasive and non-contact system for reflex-free retinal imaging and dynamic retinal vessel analysis in the rat. Theoretical analysis was performed prior to development of the new optical design, taking into account the optical properties of the rat eye and its specific illumination and imaging requirements. A novel optical model of the rat eye was developed for use with standard optical design software, facilitating both sequential and non-sequential modes. A retinal camera for the rat was constructed using standard optical and mechanical components. The addition of a customized illumination unit and existing standard software enabled dynamic vessel analysis. Seven-minute in-vivo vessel diameter recordings performed on 9 Brown-Norway rats showed stable readings. On average, the coefficient of variation was (1.1 ± 0.19) % for the arteries and (0.6 ± 0.08) % for the veins. The slope of the linear regression analysis was (0.56 ± 0.26) % for the arteries and (0.15 ± 0.27) % for the veins. In conclusion, the device can be used in basic studies of retinal vessel behavior

    Optic Nerve Head Topographic Measurements and Retinal Nerve Fiber Layer Thickness in Physiologic Large Cups

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    PURPOSE: To evaluate the parameters of optic nerve head (ONH) and retinal nerve fiber layer (RNFL) in patients with large cup/disc ratio (CDR) and normal neuroretinal rim configuration who have normal perimetry (physiologic large cups, LC) and to compare these parameters with those of the normal and early glaucoma patients. METHODS: Using Heidelberg retinal tomography (HRT) and optical coherence tomography (OCT), 30 patients with LC, 29 normal subjects, and 31 early glaucoma patients were examined. One eye from each subject was randomly selected. RESULTS: Significant differences between LC and glaucomatous eyes (GE) were found in parameters indicating loss of nerve fibers, such as rim area, rim volume, and mean RNFL thickness. However, there was no difference between LC and normal eyes (NE) in RNFL thickness, rim area, and rim volume. LC was able to be defined as a normal central excavation with a large disc and large CDR with a normal rim area. CONCLUSIONS: HRT ONH parameters and RNFL thickness obtained with OCT may be useful for differentiating between glaucoma and LC eyes.ope

    Changing views on open-angle glaucoma

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    Assessing structure and fucntion in glaucoma

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    Assessing structure and fucntion in glaucoma

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    Automatic extraction of retinal features from colour retinal images for glaucoma diagnosis: a review

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    Glaucoma is a group of eye diseases that have common traits such as, high eye pressure, damage to the Optic Nerve Head and gradual vision loss. It affects peripheral vision and eventually leads to blindness if left untreated. The current common methods of pre-diagnosis of Glaucoma include measurement of Intra-Ocular Pressure (IOP) using Tonometer, Pachymetry, Gonioscopy; which are performed manually by the clinicians. These tests are usually followed by Optic Nerve Head (ONH) Appearance examination for the confirmed diagnosis of Glaucoma. The diagnoses require regular monitoring, which is costly and time consuming. The accuracy and reliability of diagnosis is limited by the domain knowledge of different ophthalmologists. Therefore automatic diagnosis of Glaucoma attracts a lot of attention.This paper surveys the state-of-the-art of automatic extraction of anatomical features from retinal images to assist early diagnosis of the Glaucoma. We have conducted critical evaluation of the existing automatic extraction methods based on features including Optic Cup to Disc Ratio (CDR), Retinal Nerve Fibre Layer (RNFL), Peripapillary Atrophy (PPA), Neuroretinal Rim Notching, Vasculature Shift, etc., which adds value on efficient feature extraction related to Glaucoma diagnosis. © 2013 Elsevier Ltd

    Retinal vessel analysis:flicker reproducibility, methodological standardisations and practical limitations

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    The Retinal Vessel Analyser (RVA) is a commercially available ophthalmoscopic instrument capable of acquiring vessel diameter fluctuations in real time and in high temporal resolution. Visual stimulation by means of flickering light is a unique exploration tool of neurovascular coupling in the human retina. Vessel reactivity as mediated by local vascular endothelial vasodilators and vasoconstrictors can be assessed non-invasively, in vivo. In brief, the work in this thesis • deals with interobserver and intraobserver reproducibility of the flicker responses in healthy volunteers • explains the superiority of individually analysed reactivity parameters over vendorgenerated output • links in static retinal measures with dynamic ones • highlights practical limitations in the use of the RVA that may undermine its clinical usefulness • provides recommendations for standardising measurements in terms of vessel location and vessel segment length and • presents three case reports of essential hypertensives in a -year follow-up. Strict standardisation of measurement procedures is a necessity when utilising the RVA system. Agreement between research groups on implemented protocols needs to be met, before it could be considered a clinically useful tool in detecting or predicting microvascular dysfunction

    Hypertensive eye disease

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    Hypertensive eye disease includes a spectrum of pathological changes, the most well known being hypertensive retinopathy. Other commonly involved parts of the eye in hypertension include the choroid and optic nerve, sometimes referred to as hypertensive choroidopathy and hypertensive optic neuropathy. Together, hypertensive eye disease develops in response to acute and/or chronic elevation of blood pressure. Major advances in research over the past three decades have greatly enhanced our understanding of the epidemiology, systemic associations and clinical implications of hypertensive eye disease, particularly hypertensive retinopathy. Traditionally diagnosed via a clinical funduscopic examination, but increasingly documented on digital retinal fundus photographs, hypertensive retinopathy has long been considered a marker of systemic target organ damage (for example, kidney disease) elsewhere in the body. Epidemiological studies indicate that hypertensive retinopathy signs are commonly seen in the general adult population, are associated with subclinical measures of vascular disease and predict risk of incident clinical cardiovascular events. New technologies, including development of non-invasive optical coherence tomography angiography, artificial intelligence and mobile ocular imaging instruments, have allowed further assessment and understanding of the ocular manifestations of hypertension and increase the potential that ocular imaging could be used for hypertension management and cardiovascular risk stratification

    Accurate Image Analysis of the Retina Using Hessian Matrix and Binarisation of Thresholded Entropy with Application of Texture Mapping

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    In this paper, we demonstrate a comprehensive method for segmenting the retinal vasculature in camera images of the fundus. This is of interest in the area of diagnostics for eye diseases that affect the blood vessels in the eye. In a departure from other state-of-the-art methods, vessels are first pre-grouped together with graph partitioning, using a spectral clustering technique based on morphological features. Local curvature is estimated over the whole image using eigenvalues of Hessian matrix in order to enhance the vessels, which appear as ridges in images of the retina. The result is combined with a binarized image, obtained using a threshold that maximizes entropy, to extract the retinal vessels from the background. Speckle type noise is reduced by applying a connectivity constraint on the extracted curvature based enhanced image. This constraint is varied over the image according to each region's predominant blood vessel size. The resultant image exhibits the central light reflex of retinal arteries and veins, which prevents the segmentation of whole vessels. To address this, the earlier entropy-based binarization technique is repeated on the original image, but crucially, with a different threshold to incorporate the central reflex vessels. The final segmentation is achieved by combining the segmented vessels with and without central light reflex. We carry out our approach on DRIVE and REVIEW, two publicly available collections of retinal images for research purposes. The obtained results are compared with state-of-the-art methods in the literature using metrics such as sensitivity (true positive rate), selectivity (false positive rate) and accuracy rates for the DRIVE images and measured vessel widths for the REVIEW images. Our approach out-performs the methods in the literature.Xiaoxia Yin, Brian W-H Ng, Jing He, Yanchun Zhang, Derek Abbot
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