| 基于SVM-2DPCA的X光胸片异常筛查 |
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| 引用本文： | 王彦明,钱建忠,潘晨. 基于SVM-2DPCA的X光胸片异常筛查[J]. 计算机工程, 2009, 35(18): 170-172 |
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| 作者姓名： | 王彦明 钱建忠 潘晨 |
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| 作者单位： | 宁夏大学数学计算机学院,银川,750021;银川市第二人民医院放射科,银川,750001 |
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| 基金项目： | 国家自然科学基金资助项目，宁夏自然科学基金资助项目 |
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| 摘 要： | 基于统计学习理论的支持向量机分类算法，提出一种X光胸片异常筛查系统，能够自动判别胸片的正常和异常。为了提高SVM算法的效率，利用小波变换等预处理手段去除对判读无用的图像冗余信息，采用二维主成分分析进一步降低图像特征维数。实验结果表明，SVM用于医学X光片异常筛查可行且有效、识别率高。
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| 关 键 词： | X光片 图像分类 支持向量机 二维主成分分析 |
| 修稿时间： | |
Abnormality Judgment of X-ray Chest File Based on SVM-2DPCA |
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| WANG Yan-ming,QIAN Jian-zhong,PAN Chen. Abnormality Judgment of X-ray Chest File Based on SVM-2DPCA[J]. Computer Engineering, 2009, 35(18): 170-172 |
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| Authors: | WANG Yan-ming QIAN Jian-zhong PAN Chen |
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| Affiliation: | 1.School of Mathematics and Computer Science;Ningxia University;Yinchuan 750021;2.Radioactive Bureau;The Second People's Hospital of Ningxia;Yinchuan 750001 |
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| Abstract: | Based on Support Vector Machine(SVM), the system for the abnormality judgment of X-ray chest file is presented, which can classify the X-ray picture normal and abnormal automatically.In order to improve the efficiency of the SVM, the wavelet transform is adopted in the system to eliminate the redundancy information in image.Two-Dimensional Principal Component Analysis(2DPCA) is used for feature extraction.Experimental results show that the SVM-based method is feasible in X-ray abnormality judgment, and has ... |
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| Keywords: | X-ray file image classification Support Vector Machine(SVM) Two-Dimensional Principal Component Analysis(2DPCA) |
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