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Method for the Automatic Segmentation of the Palpebral Conjunctiva using Image Processing

机译:图像处理自动分割睑结膜的方法

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Conventional methods to diagnose anemia require a blood draw. This generates a great problem in patients due to the fear of contracting a disease through syringes, or sensitivity to this element. The palpebral conjunctiva is an indicator of diseases such as the hordeolum, chalazion, marginal blepharitis, bacterial conjunctivitis, trachoma, and anemia. The palpebral conjunctiva pallor is an indicator of anemia and if we wanted to develop an automatic system, for the non-invasive diagnosis of anemia based on the analysis of photographs of the palpebral conjunctiva, we would need algorithms for the segmentation and analysis of this membrane. In this sense, this research proposes and develops a method for the automatic segmentation of the palpebral conjunctiva using an Android application and image processing techniques. As a result, the success of this segmentation method is 92.2%.
机译:诊断贫血的常规方法需要抽血。由于担心通过注射器感染疾病或对该元素的敏感性,这在患者中产生了很大的问题。睑结膜是诸如大麦,睑缘炎,边缘性睑缘炎,细菌性结膜炎,沙眼和贫血等疾病的指标。睑结膜苍白是贫血的指标,如果我们想开发一个自动系统,用于基于睑结膜照片分析的无创性贫血诊断,我们将需要用于该膜的分割和分析的算法。从这个意义上讲,这项研究提出并开发了一种使用Android应用程序和图像处理技术自动分割睑结膜的方法。结果,该分割方法的成功率为92.2%。

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