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Classification of Outer Retinal Layers Based on KNN-Classifier

机译:基于KNN分类器的视网膜外层分类

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摘要

Eyes are the organs of the visual system. The eyes are affected by eye diseases causing loss of vision. Retinitis Pigmentosa is a genetic condition which is passed down to families and it varies from person to person. Segmentation (Automatic) of external retinal layers is challenging because of the resolution of the human eye. This paper proposes a technique to classify the external retinal layers by means of KNN. It helps doctors to plan on further treatment. To segment the external layers in the retina by applying different preprocessing steps. To detect the region of interest(outer retina) the pre-processing step is performed. Second, few Framework parameters of the outer retina are calculated by fitting the candidate models. To select the Framework supported by the data Framework resolution technique is required by model selection. The detected layers are assigned by the labels (layer identification). Finally, classification by (KNN) to decide whether or not the eye's is in normal or in abnormal condition.
机译:眼睛是视觉系统的器官。眼睛受到导致视力丧失的眼疾的影响。色素性视网膜炎是一种遗传病,会遗传给家庭,并且因人而异。由于人眼的分辨率,视网膜外层的分割(自动)是一项挑战。本文提出了一种利用KNN对视网膜外层进行分类的技术。它可以帮助医生计划进一步的治疗。通过应用不同的预处理步骤来分割视网膜中的外层。为了检测感兴趣的区域(视网膜外部),执行预处理步骤。其次,通过拟合候选模型来计算很少的外部视网膜框架参数。要选择数据支持的框架,模型选择需要框架解析技术。检测到的层由标签分配(层标识)。最后,用(KNN)进行分类,以决定眼睛是否处于正常或异常状态。

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