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An Approach to Retinal Image Segmentations Using Fuzzy Clustering in Combination with Morphological Filters

机译:模糊聚类结合形态学滤波的视网膜图像分割方法

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Retinal vessel appearance is an important feature for personal identification, information security and confidentiality. It also is a key indicator for many early diagnoses, such as diabetes and hypertension. In this approach, a extraction method of retinal vessels based on fuzzy clustering in combination with morphological filtering is proposed. By decomposing the green channel image into smooth and textured components, fuzzy clustering is firstly performed on the textured composite, then the morphological open operation with multiscale linear-like structure elements is applied to suppressing noise structure. Experimental results indicate that the method can automatically and effectively extract most of the vessel backbones and branches.
机译:视网膜血管的外观是个人识别,信息安全和机密性的重要特征。它也是许多早期诊断的关键指标,例如糖尿病和高血压。提出了一种基于模糊聚类结合形态学滤波的视网膜血管提取方法。通过将绿色通道图像分解为平滑和纹理化的成分,首先对纹理化的合成物进行模糊聚类,然后应用具有多尺度线性结构元素的形态学开放操作来抑制噪声结构。实验结果表明,该方法可以自动有效地提取出大部分的血管骨架和分支。

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