matlab代码影响-RetinalVesselDection:视网膜血管病变

上传者: 38679651 | 上传时间: 2023-03-25 13:18:34 | 文件大小: 8.25MB | 文件类型: ZIP
matlab代码影响视网膜血管病变 视网膜血管检查在糖尿病的诊断中起着重要的作用,在西方国家,糖尿病是导致失明的主要原因。 该检查采用光学诊断方法,通过获取眼球的数字图像而不会侵犯或伤害人体。 剩下的任务是将视网膜血管与数字图像分开。 即使对于训练有素的专家来说,这都是耗时且充满挑战的。 引入了机器学习方法以使分离过程自动化,从而提高检查过程的效率。 在本报告中,我们结合了图像处理和机器学习方法探索了视网膜血管分离过程。 图像预处理用于减少原始眼球图像中的噪点。 机器学习算法用于构造分类器,该分类器利用专家的手绘视网膜血管作为训练标签,以有效地将血管与背景分离。 实现了K最近邻(K-NN)和支持向量机(SVM),并使用改进的K-NN方法来改善结果。 使用K-NN方法中距离的不同定义来发现眼球图像不同特征的重要性。 通过将算法分类的标签与专家的手绘图像进行比较,可以估算出误差。 K-NN是通过使用在课堂上学到的知识而自编码的Matlab程序,并且SVM在理论层面上得到了理解,并通过PyML(基于python的机器学习包)来实现。 两种方法的错误率均为6%左右。 与SVM相比,K-NN产生

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