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The Classification of Meningioma Subtypes Based on the Color Segmentation and Shape Features

机译:基于颜色分割和形状特征的脑膜瘤亚型分类

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This paper proposed an automatic method tor the classification of meningioma subtypes based on the unsupervised color segmentation method and feature selection scheme. Firstly, a color segmentation method is utilized to segment the cell nuclei. Then the set of shape feature vectors which are calculated from the segmentation results are constructed. Finally, a k-nearest neighbour classifier (kNN) is used to classify the meningioma subtypes. Experiment shows that the classification accuracy of 85 % is achieved by using a leave-one-out cross validation approach on 80 meningioma images.
机译:本文提出了一种基于无监督颜色分割方法和特征选择方案的脑膜瘤亚型分类自动方法。首先,采用颜色分割方法对细胞核进行分割。然后构造根据分割结果计算出的一组形状特征向量。最后,使用k近邻分类器(kNN)对脑膜瘤亚型进行分类。实验表明,通过对80例脑膜瘤图像使用留一法交叉验证方法,可以达到85%的分类精度。

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