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Disease Discrimination based on Disease Subspace of Organ Shape Using Orthogonal Complement of Normal Subspace

机译:基于常规子空间的正交补充基于器官形状疾病子空间的疾病歧视

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Diagnostic modeling based on computational anatomy is an important topic. In previous work, discrimination method using support vector machine based on principal component analysis of the hippocampus shapes have been proposed. However, disease-specific component was not considered explicitly. In this paper, we propose a method for constructing the disease subspace using orthogonal complement of the normal subspace. The proposed method was tested using the hepatic cirrhosis and hip osteoarthritis datasets and was compared to a previous method. In our experiments, the proposed method was effective for disease discrimination based on organ shapes.
机译:基于计算解剖学的诊断建模是一个重要的主题。 在以前的工作中,提出了基于基于海马形状的主成分分析的支持向量机的辨别方法。 然而,疾病特异性组分未明确考虑。 在本文中,我们提出了一种使用正常子空间的正交补充构建疾病子空间的方法。 使用肝硬化和髋关节骨关节痉挛测试该方法,并与先前的方法进行了测试。 在我们的实验中,所提出的方法对于基于器官形状的疾病歧视是有效的。

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