Automated retinal analysis

Diabetes is a chronic disease affecting over 2% of the population in the UK [1]. Long-term complications of diabetes can affect many different systems of the body including the retina of the eye. In the retina, diabetes can lead to a disease called diabetic retinopathy, one of the leading causes of blindness in the working population of industrialised countries. The risk of visual loss from diabetic retinopathy can be reduced if treatment is given at the onset of sight-threatening retinopathy. To detect early indicators of the disease, the UK National Screening Committee have recommended that diabetic patients should receive annual screening by digital colour fundal photography [2]. Manually grading retinal images is a subjective and costly process requiring highly skilled staff. This thesis describes an automated diagnostic system based oil image processing and neural network techniques, which analyses digital fundus images so that early signs of sight threatening retinopathy can be identified. Within retinal analysis this research has concentrated on the development of four algorithms: optic nerve head segmentation, lesion segmentation, image quality assessment and vessel width measurements. This research amalgamated these four algorithms with two existing techniques to form an integrated diagnostic system. The diagnostic system when used as a 'pre-filtering' tool successfully reduced the number of images requiring human grading by 74.3%: this was achieved by identifying and excluding images without sight threatening maculopathy from manual screening

A robust lesion boundary segmentation algorithm using level set methods

This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and a novel stopping mechanism - an elementary features scheme. Specifically, the curve propagation is guided by a gradient map built using a combination of histogram equalization and robust statistics. The stopping mechanism uses elementary features gathered as the curve deforms over time, and then using a lesionness measure, defined herein, ’looks back in time’ to find the point at which the curve best fits the real object. We compare the proposed method against five other segmentation algorithms performed on 50 randomly selected images of exudates with a database of clinician demarcated boundaries as ground truth

A GPU-based Evolution Strategy for Optic Disk Detection in Retinal Images

La ejecución paralela de aplicaciones usando unidades de procesamiento gráfico (gpu) ha ganado gran interés en la comunidad académica en los años recientes. La computación paralela puede ser aplicada a las estrategias evolutivas para procesar individuos dentro de una población, sin embargo, las estrategias evolutivas se caracterizan por un significativo consumo de recursos computacionales al resolver problemas de gran tamaño o aquellos que se modelan mediante funciones de aptitud complejas. Este artículo describe la implementación de una estrategia evolutiva para la detección del disco óptico en imágenes de retina usando Compute Unified Device Architecture (cuda). Los resultados experimentales muestran que el tiempo de ejecución para la detección del disco óptico logra una aceleración de 5 a 7 veces, comparado con la ejecución secuencial en una cpu convencional.Parallel processing using graphic processing units (GPUs) has attracted much research interest in recent years. Parallel computation can be applied to evolution strategy (ES) for processing individuals in a population, but evolutionary strategies are time consuming to solve large computational problems or complex fitness functions. In this paper we describe the implementation of an improved ES for optic disk detection in retinal images using the Compute Unified Device Architecture (CUDA) environment. In the experimental results we show that the computational time for optic disk detection task has a speedup factor of 5x and 7x compared to an implementation on a mainstream CPU

Lesion boundary segmentation using level set methods

This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and a novel stopping mechanism - an elementary features scheme. Specifically, the curve propagation is guided by a gradient map built using a combination of histogram equalization and robust statistics. The stopping mechanism uses elementary features gathered as the curve deforms over time, and then using a lesionness measure, defined herein, ’looks back in time’ to find the point at which the curve best fits the real object. We implement the level set using a fast upwind scheme and compare the proposed method against five other segmentation algorithms performed on 50 randomly selected images of exudates with a database of clinician marked-up boundaries as ground truth

Linking recorded data with emotive and adaptive computing in an eHealth environment

Telecare, and particularly lifestyle monitoring, currently relies on the ability to detect and respond to changes in individual behaviour using data derived from sensors around the home. This means that a significant aspect of behaviour, that of an individuals emotional state, is not accounted for in reaching a conclusion as to the form of response required. The linked concepts of emotive and adaptive computing offer an opportunity to include information about emotional state and the paper considers how current developments in this area have the potential to be integrated within telecare and other areas of eHealth. In doing so, it looks at the development of and current state of the art of both emotive and adaptive computing, including its conceptual background, and places them into an overall eHealth context for application and development

Simple non-mydriatic retinal photography is feasible and demonstrates retinal microvascular dilation in Chronic Obstructive Pulmonary Disease (COPD).

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is associated with an increased risk of myocardial infarction and stroke but it remains unclear how to identify microvascular changes in this population. OBJECTIVES: We hypothesized that simple non-mydriatic retinal photography is feasible and can be used to assess microvascular damage in COPD. METHODS: Novel Vascular Manifestations of COPD was a prospective study comparing smokers with and without COPD, matched for age. Non-mydriatic, retinal fundus photographs were assessed using semi-automated software. RESULTS: Retinal images from 24 COPD and 22 control participants were compared. Cases were of similar age to controls (65.2 vs. 63.1 years, p = 0.38), had significantly lower Forced Expiratory Volume in one second (FEV1) (53.4 vs 100.1% predicted; p < 0.001) and smoked more than controls (41.7 vs. 29.6 pack years; p = 0.04). COPD participants had wider mean arteriolar (155.6 ±15 uM vs. controls [142.2 ± 12 uM]; p = 0.002) and venular diameters (216.8 ±20.7 uM vs. [201.3± 19.1 uM]; p = 0.012). Differences in retinal vessel caliber were independent of confounders, odds ratios (OR) = 1.08 (95% confidence intervals [CI] = 1.02, 1.13; p = 0.007) and OR = 1.05 (CI = 1.01, 1.09; p = 0.011) per uM increase in arteriolar and venular diameter respectively. FEV1 remained significantly associated with retinal vessel dilatation r = -0.39 (p = 0.02). CONCLUSIONS: Non-mydriatic retinal imaging is easily facilitated. We found significant arteriole and venous dilation in COPD compared to age-matched smokers without COPD associated with lung function independent of standard cardiovascular risk factors. Retinal microvascular changes are known to be strongly associated with future vascular events and retinal photography offers potential to identify this risk. TRIAL REGISTRATION: clinicaltrials.gov NCT02060292

Vascular Response to Sildenafil Citrate in Aging and Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) - the leading cause of vision loss in the elderly - share many risks factors as atherosclerosis, which exhibits loss of vascular compliance resulting from aging and oxidative stress. Here, we attempt to explore choroidal and retinal vascular compliance in patients with AMD by evaluating dynamic vascular changes using live ocular imaging following treatment with oral sildenafil citrate, a phosphodiesterase type 5 (PDE5) inhibitor and potent vasodilator. Enhanced-depth imaging optical coherence tomography (EDI-OCT) and OCT angiography (OCT-A) were performed on 46 eyes of 23 subjects, including 15 patients with non-exudative AMD in one eye and exudative AMD in the fellow eye, and 8 age-matched control subjects. Choroidal thickness, choroidal vascularity, and retinal vessel density were measured across the central macula at 1 and 3 hours after a 100 mg oral dose of sildenafil citrate. Baseline choroidal thickness was 172.1 ± 60.0 μm in non-exudative AMD eyes, 196.4 ± 89.8 μm in exudative AMD eyes, and 207.4 ± 77.7 μm in control eyes, with no difference between the 3 groups (P = 0.116). After sildenafil, choroidal thickness increased by 6.0% to 9.0% at 1 and 3 hours in all groups (P = 0.001-0.014). Eyes from older subjects were associated with choroidal thinning at baseline (P = 0.005) and showed less choroidal expansion at 1 hour and 3 hours after sildenafil (P = 0.001) regardless of AMD status (P = 0.666). The choroidal thickening appeared to be primarily attributed to expansion of the stroma rather than luminal component. Retinal vascular density remained unchanged after sildenafil in all 3 groups (P = 0.281-0.587). Together, our studies suggest that vascular response of the choroid to sildenafil decreases with age, but is not affected by the presence of non-exudative or exudative AMD, providing insight into changes in vessel compliance in aging and AMD

Effect of Uveal Melanocytes on Choroidal Morphology in Rhesus Macaques and Humans on Enhanced-Depth Imaging Optical Coherence Tomography.

PurposeTo compare cross-sectional choroidal morphology in rhesus macaque and human eyes using enhanced-depth imaging optical coherence tomography (EDI-OCT) and histologic analysis.MethodsEnhanced-depth imaging-OCT images from 25 rhesus macaque and 30 human eyes were evaluated for choriocapillaris and choroidal-scleral junction (CSJ) visibility in the central macula based on OCT reflectivity profiles, and compared with age-matched histologic sections. Semiautomated segmentation of the choriocapillaris and CSJ was used to measure choriocapillary and choroidal thickness, respectively. Multivariate regression was performed to determine the association of age, refractive error, and race with choriocapillaris and CSJ visibility.ResultsRhesus macaques exhibit a distinct hyporeflective choriocapillaris layer on EDI-OCT, while the CSJ cannot be visualized. In contrast, humans show variable reflectivities of the choriocapillaris, with a distinct CSJ seen in many subjects. Histologic sections demonstrate large, darkly pigmented melanocytes that are densely distributed in the macaque choroid, while melanocytes in humans are smaller, less pigmented, and variably distributed. Optical coherence tomography reflectivity patterns of the choroid appear to correspond to the density, size, and pigmentation of choroidal melanocytes. Mean choriocapillary thickness was similar between the two species (19.3 ± 3.4 vs. 19.8 ± 3.4 μm, P = 0.615), but choroidal thickness may be lower in macaques than in humans (191.2 ± 43.0 vs. 266.8 ± 78.0 μm, P &lt; 0.001). Racial differences in uveal pigmentation also appear to affect the visibility of the choriocapillaris and CSJ on EDI-OCT.ConclusionsPigmented uveal melanocytes affect choroidal morphology on EDI-OCT in rhesus macaque and human eyes. Racial differences in pigmentation may affect choriocapillaris and CSJ visibility, and may influence the accuracy of choroidal thickness measurements