| 基于SVM的医学图像分类器的设计 |
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| 引用本文： | 华翔,孙蕾.基于SVM的医学图像分类器的设计[J].微电子学与计算机,2011,28(6). |
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| 作者姓名： | 华翔 孙蕾 |
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| 作者单位： | 1. 西安工业大学,电子信息工程学院,陕西,西安,710032
2. 西安电子科技大学,陕西,西安,710071 |
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| 摘 要： | 提出了一个基于支持向量机的医学图像分类器.能提取形状和纹理特征作为分类算法的特征输入,进行计算机辅助诊断.提出了一种支持向量机新算法,解决了当两类中的样本数量差别较大时,支持向量机的分类能力将会下降的问题.实验表明,在小样本、两类样本数量严重不均衡的情况下,该算法有着较强的分类能力,可以极大地提高医学图像分类的效率和准确性.
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| 关 键 词： | 支持向量机 医学图像分类 特征提取 图像分割 梯度矢量流 |
Design of Medical Image Classifier Based on SVM |
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| HU Xiang,SUN Lei.Design of Medical Image Classifier Based on SVM[J].Microelectronics & Computer,2011,28(6). |
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| Authors: | HU Xiang SUN Lei |
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| Abstract: | A medical image classifier is proposed in this paper.Gradient Vector Flow(GVF) is used to segment tumor area,and the texture and shape features are the inputs to classifier.A novel SVM algorithm is presented in this paper,which solves the problem that SVM has a poor performance when the two-class problem samples are very unbalanced.The experimental results indicate that the modified algorithm has a strong capability of classification for the unbalanced samples,and the efficiency and accuracy in the medical ... |
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| Keywords: | SVM medical image classifier feature extraction image segmentation Gradient Vector Flow |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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