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A Novel Framework for Hyperemia Grading Based on Artificial Neural Networks

机译:基于人工神经网络的充血分级新框架

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A common symptom of several pathologies is hyperemia, that occurs when a certain tissue has an abnormal hue of red. An increase of blood flow causes the engorgement of blood vessels, which produces the coloration. Hyperemia is an important parameter that specialists take into account when diagnosing diseases such as dry eye syndrome or problems derived from contact lenses wearing. In this work, we propose an automatic methodology to measure the hyperemia level of the bulbar conjunctiva. This methodology emphasizes the transformation from the extracted features to grading scales, using artificial neural networks for the process.
机译:几种病理的常见症状是充血,充血发生在某些组织具有异常的红色调时。血流量的增加引起血管充血,从而产生颜色。充血是诊断干眼症或戴隐形眼镜引起的问题等疾病时,专家要考虑的重要参数。在这项工作中,我们提出了一种自动方法来测量球结膜充血水平。这种方法强调了使用人工神经网络进行从提取特征到分级标度的转换。

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