德鲁森
黄斑变性
人工智能
支持向量机
眼底(子宫)
计算机科学
计算机视觉
对比度(视觉)
模式识别(心理学)
光学相干层析成像
图像处理
图像(数学)
眼科
医学
作者
Andrés García Floriano,Ángel Ferreira-Santiago,Oscar Camacho-Nieto,Cornelio Yáñez-Márquez
标识
DOI:10.1016/j.compeleceng.2017.11.008
摘要
Age-Related Macular Degeneration (AMD) is a dangerous, chronic, and progressive illness that mostly affects people over 60 years old. This disease is related to the appearance of drusen: deposits of extracellular material located in the macular region. One way to effectively and non-invasively pre-diagnose AMD is by detecting the presence of drusen in fundus images. In this work we propose a new method that combines Digital Image Processing, Mathematical Morphology and a robust and powerful Machine Learning model: a Support Vector Machine (SVM). The enclosed macular region is subjected to a contrast enhancement method, followed by the application of basic morphological operations. We use invariant moments as the features of the processed image. The resulting vector is classified by an SVM as positive or negative for drusen. The proposed method is able to discriminate between healthy and afflicted cases with a classification accuracy that outperforms many well-regarded state-of-the-art methods.
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