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A Novel Method of Detecting and Locating the Macula Based on Morphological Features Fitting

机译:一种基于形态特征拟合的检测和定位黄斑的一种新方法

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Color retinal images have been widely used in diagnosis and screening of ophthalmic diseases. Macula detection and fovea location in retinal images are important steps in grading and diagnosis of ophthalmic diseases. However, due to the weaker reflection of the macula, it is difficult to determine the fovea accurately by the lack of clear border in the macula. An efficient method for detecting and locating macula based on morphological features fitting is proposed. The macula area is detected by its low brightness and round shape features. And then the K-means clustering and circle fitting is applied to achieve accurate position of macular center. A series of tests show good performance in the public retinal images database. Thus the proposed method based on morphological features fitting is proved to be efficient and useful for computer-aided diagnosis of ocular diseases.
机译:彩色视网膜图像已被广泛用于眼科疾病的诊断和筛选。视网膜图像中的黄斑检测和FoVEA位置是眼科疾病的分级和诊断的重要步骤。然而,由于黄斑的反射较弱,难以通过缺乏斑块的透明边界来准确地确定FOVEA。提出了一种基于形态特征拟合的检测和定位黄斑的有效方法。通过其低亮度和圆形特征来检测黄斑区域。然后应用K-means聚类和圆拟合来实现Matular中心的准确位置。一系列测试在公共视网膜图像数据库中表现出良好的性能。因此,基于形态特征拟合的提出方法被证明是高效可用于眼部疾病的计算机辅助诊断。

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