| 引用本文: | 丁建睿,黄剑华,刘家锋,张英涛.基于mRIVIR和SVM的弹性图像特征选择与分类[J].哈尔滨工业大学学报,2012,44(5):81.DOI:10.11918/j.issn.0367-6234.2012.05.016 |
| DING Jian-rui,HUANG Jian-hua,LIU Jia-feng,ZHANG Ying-tao.Elastogram features selection and classification based on mRMR and SVM[J].Journal of Harbin Institute of Technology,2012,44(5):81.DOI:10.11918/j.issn.0367-6234.2012.05.016 |
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| 摘要: |
| 为客观的评价弹性图像，利用图像处理与模式识别技术进行分析．首先通过彩色变换获取弹性信
息，然后提取弹性图像用户感兴趣区域的一阶统计特征和纹理特征，采用“最小冗余最大相关”( mRMR)算
法选择优化的特征，最后使用带有核函数的SVM分类器对弹性图像进行分类．实验结果表明：该方法具有较
高的准确率(92%)．采用计算机辅助诊断技术对弹性图像进行定量分析可有助于提高诊断准确率 |
| 关键词: 弹性图像 纹理 特征选择 最小冗余最大相关 支持向量机 |
| DOI：10.11918/j.issn.0367-6234.2012.05.016 |
| 分类号:TP391 |
| 基金项目:国家自然科学基金资助项目(60873142)；哈尔滨市优
秀学科带头人资助项目( 2009RFXXS211) |
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| Elastogram features selection and classification based on mRMR and SVM |
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DING Jian-rui, HUANG Jian-hua, LIU Jia-feng, ZHANG Ying-tao
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School of Computer Science and Engineering, Harbin Institute of Technology, 150001 Harbin, China
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| Abstract: |
| For evaluating elastogram objectively, image processing and pattern recogniton techniques are pro-
posed. First the real elasticity information encoded in color was extracted by transform the image from RGB
color space to HSV space. Then the statistical features and texture features were extracted from region of inter-
est on the elastogram. The important and reliable features were selected by using Minimum-Redundancy-Maxi-
mum-Relevance ( mRMR) algorithm. Finally the selected features were input to the SVM classifier to classify
the thyroid nodules into benign and malignant. The experiment results confirmed the method had higher accu-
racy (92% ). It is helpful to improve the clinical accuracy by using CAD techniques |
| Key words: elastogram texture feature selection Minimum-Redundancy-Maximum-Relevance support vec-
tor machine |
