A Computer Vision Approach Based on the Retinal Nerve Fiber Thickness Analysis to Estimate the Risk of Suffering Glaucoma

M. Chazi-Solis, C. Cajamarca-Bueno, E. Pinos-Vélez, V. Robles-Bykbaev, C. Chacón
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引用次数: 1

Abstract

According to estimations of the World Health Organization (WHO), approximately 4.5 million persons will become blind due to the primary Glaucoma. For these reasons, in this paper, we present a simple approach to estimate the risk of suffering from glaucoma that presents a patient. Our proposal relies on the automatic analysis of Optical Coherence Tomography (OCT) images through the calculus of nerve fiber and ganglionary vessels areas. To this aim, our system separates the two areas mentioned before through computer vision techniques and the Newton Interpolation Method. Once the two areas are separated, the system determines the size of each of them. This proposal was validated through an experiment carried out with OCT 30 images (per eye). The results are encouraging, and the suggestions provided by the system match with medical diagnosis.
基于视网膜神经纤维厚度分析的计算机视觉方法评估青光眼风险
根据世界卫生组织(卫生组织)的估计,大约有450万人将因原发性青光眼而失明。由于这些原因,在本文中,我们提出了一个简单的方法来估计患青光眼的风险,提出了一个病人。我们的建议依赖于通过神经纤维和神经节血管区域演算的光学相干断层扫描(OCT)图像的自动分析。为此,我们的系统通过计算机视觉技术和牛顿插值方法分离了前面提到的两个区域。一旦这两个区域被分开,系统就会决定每个区域的大小。通过OCT 30图像(每只眼睛)进行的实验验证了这一建议。结果令人鼓舞,系统提供的建议与医学诊断相匹配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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