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Full-Automatic Optic Disc Boundary Extraction Based on Modified Local Binary Fitting Model in Retinal Image

机译:基于改进的局部二值拟合模型的视网膜图像全自动光盘边界提取

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Accurate optic disc (OD) segmentation plays a significant role for retinal disease diagnosis. In this paper, a full-automatic segmentation approach named double boundary extraction for the OD segmentation is proposed. It is consisted of two main stages: first, the satisfying initial level set contour for OD boundary is extracted by an adaptive method based on unsupervised learning technology and statistical method; second, the proposed LSO model combined with prior information of OD can effectively obtain the final OD boundary. Extensive experiments on the publicly available DIARETDB 1 database demonstrate that the proposed method has the advantage over the state-of-the-art methods.
机译:准确的视盘(OD)分割在视网膜疾病诊断中起着重要作用。本文提出了一种用于OD分割的全自动分割方法,称为双边界提取。它包括两个主要阶段:第一,通过基于无监督学习技术和统计方法的自适应方法,提取出满足OD边界的初始水平集轮廓。其次,所提出的LSO模型结合OD的先验信息可以有效地获得最终的OD边界。在公开可用的DIARETDB 1数据库上进行的大量实验表明,与现有技术相比,该方法具有优势。

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