首页> 美国卫生研究院文献>Journal of Clinical Medicine >A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography
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A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography

机译:一种使用扫频光学相干断层扫描血管成像技术估算视力并分析视网膜静脉阻塞的视网膜血管的自动方法

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摘要

The assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze image features and correlate them with visual function. The aim of this study is to propose a fully automatic system which is capable of estimating visual acuity (VA) in RVO eyes, based only on information obtained from macular optical coherence tomography angiography (OCTA) images. We also propose an automatic methodology to rapidly measure the foveal avascular zone (FAZ) area and the vascular density (VD) in the superficial and deep capillary plexuses in swept-source OCTA images centered on the fovea. The proposed methodology is validated using a representative sample of 133 visits of 50 RVO patients. Our methodology estimates VA with very high precision and is even more accurate when we integrate depth information, providing a high correlation index of 0.869 with the real VA, which outperforms the correlation index of 0.855 obtained when estimating VA from the data obtained by the semiautomatic existing method. In conclusion, the proposed method is the first computational system able to estimate VA in RVO, with the additional benefits of being automatic, less time-consuming, objective and more accurate. Furthermore, the proposed method is able to integrate depth information, a feature which is lacking in the existing method.
机译:在视网膜静脉阻塞(RVO)的诊断和随访中,评估血管生物标记及其与视敏度的关系是最重要的问题之一。临床实践的高工作量使得必须有一种快速,客观和自动的方法来分析图像特征并将其与视觉功能相关联。这项研究的目的是提出一种全自动系统,该系统能够仅基于从黄斑光学相干断层扫描血管造影(OCTA)图像获得的信息来估计RVO眼睛的视敏度(VA)。我们还提出了一种自动方法,可以快速测量以中央凹为中心的扫掠源OCTA图像中的浅凹和深层毛细血管丛的中央凹无血管区域(FAZ)面积和血管密度(VD)。使用50名RVO患者的133次就诊的代表性样本验证了所提出的方法。我们的方法以很高的精度估算VA,并且在集成深度信息时甚至更准确,与真实VA提供高的相关系数0.869,优于从半自动现有数据中估算VA时获得的相关系数0.855。方法。总之,所提出的方法是第一个能够估计RVO中VA的计算系统,它具有自动,耗时少,客观且更准确的附加优点。此外,所提出的方法能够整合深度信息,这是现有方法所缺乏的特征。

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