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Novel methods in retinal vessel calibre feature extraction for systemic disease assessment

机译:用于全身疾病评估的视网膜血管口径特征提取的新方法

摘要

Retina and its vascular network have unique branching characteristics morphology of which will change as a result of some systemic diseases, including hypertension, stroke and diabetes. Therefore, retinal image has been used as non-invasive screening window for risk assessment and prediction of such disease condition especially at the baseline. The assessment is based on a number of features among which vessel diameter (both individual and summary) and fractal dimension (FD) are the ones mostly associated with risk of diabetes and stroke. The association is linked to the higher risk of diabetes and stroke in people with narrower retinal arteriole diameter or change in overall fractal dimension independent of any risk factor (i.e. blood pressure, cardiovascular risk factors). Diameter measurement requires vessel edges to be located and tracked however; accurate edge perception is subject to image contrast, shadows, lighting condition and even presence of retinopathy legions close to vessel boundaries. This will lead to imprecision and inconsistencies between different automatic measurement techniques and may affect the significance of its association with disease condition in risk-assessment studies. As accuracy and success of diameter measurement is subject to large variations due to image artifacts it may not be suitable for fully automatic applications. In order to compensate for such error, at first two novel automatic vessel diameter measurement techniques were proposed and validated which were more robust in the presence of such image artifacts compared to similar methods. However, sometimes the exact edge location and actual diameter value is not of interest. In most case-control studies, it is of importance to comparatively evaluate the variations in retinal vessel diameter as a sign of retinopathy such as arteriolar nicking as an example of hypertensive retinopathy. Vessel diameter is often required to be compared with a reference value in many analytical assessments for diagnostic purpose. This includes monitoring the diameter variations of a specific vessel segment within single subject overtime or across multiple subjects. This helps ophthalmologists to understand whether it has undergone any significant change and perhaps associate it with a disease abnormality. A technique that can effectively quantify that change without being impaired by image artifacts is of more importance and one of the rationales of this study. This research hypothesized an edge independent solution for quantifying diameter variations when the actual diameter value is not required and proposed a new feature based on fractal analysis of vessel cross-section profile as a time series signal. This feature provides a link between FD as a global measure of the complexity and diameter variation as local property of a specific vessel segment. The clinical application of this feature has been validated on two population studies which showed promising result for assessment of mild non-proliferative diabetic retinopathy and 10-year stroke. This research work has also investigated whether the FD of retinal microvasculature would be affected by cyclic pulsations of retinal vessels and whether ECG synchronization is required prior to taking fundus images to compensate for this potential source of variations.
机译:视网膜及其血管网络具有独特的分支特征,其形态会因某些系统性疾病(包括高血压,中风和糖尿病)而改变。因此,视网膜图像已被用作非侵入性筛查窗口,用于风险评估和这种疾病状况的预测,尤其是在基线时。评估基于许多特征,其中血管直径(既包括个体直径又包括摘要)和分形维数(FD)是与糖尿病和中风风险最相关的特征。这种关联与视网膜小动脉直径狭窄或总分形维数变化的人群中罹患糖尿病和中风的风险较高有关,而与任何危险因素(即血压,心血管疾病危险因素)无关。直径测量需要定位和跟踪血管边缘。准确的边缘感知会受到图像对比度,阴影,光照条件甚至靠近血管边界的视网膜病变军团的影响。这将导致不同自动测量技术之间的不精确和不一致,并可能影响其与疾病状况相关联的风险评估研究的重要性。由于图像伪影,直径测量的准确性和成功会发生很大的变化,因此可能不适合全自动应用。为了补偿这样的误差,首先提出并验证了两种新颖的自动血管直径测量技术,与类似方法相比,它们在存在这种图像伪像的情况下更加鲁棒。但是,有时不需要精确的边缘位置和实际直径值。在大多数病例对照研究中,重要的是比较评估视网膜血管直径的变化,以作为视网膜病变的征兆,例如小动脉切开是高血压视网膜病变的一个例子。在许多分析评估中,出于诊断目的,通常需要将容器直径与参考值进行比较。这包括在单个受试者加班或跨多个受试者的过程中监视特定血管段的直径变化。这有助于眼科医生了解其是否发生了任何重大变化,并可能将其与疾病异常相关联。能够有效地量化变化而不受图像伪影影响的技术更为重要,也是这项研究的基本原理之一。这项研究假设当不需要实际直径值时可以采用边缘无关的解决方案来量化直径变化,并基于脉管横截面轮廓的分形分析作为时间序列信号提出了一种新功能。此功能在FD(作为复杂性的整体度量)与直径变化(作为特定血管段的局部属性)之间建立了联系。此功能的临床应用已在两项人群研究中得到验证,这些研究显示出可用于评估轻度非增殖性糖尿病性视网膜病变和10年卒中的有希望的结果。这项研究工作还调查了视网膜微脉管系统的FD是否会受到视网膜血管循环脉动的影响,以及在拍摄眼底图像以补偿这种潜在变异源之前是否需要ECG同步。

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    Aliahmad B;

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