| 基于支持向量机的~(31)P磁共振波谱肝细胞癌诊断 |
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| 引用本文： | 付婷婷,刘毅慧,刘强,李保朋,成金勇. 基于支持向量机的~(31)P磁共振波谱肝细胞癌诊断[J]. 生物信息学, 2010, 8(1): 20-22 |
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| 作者姓名： | 付婷婷 刘毅慧 刘强 李保朋 成金勇 |
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| 作者单位： | 1. 山东轻工业学院,信息科学与技术学院,智能信息处理研究所,山东,济南,250353
2. 山东省医学影像学研究所,山东,济南,250021 |
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| 基金项目： | 山东省自然科学基金,山东省自然科学基金,SRF for ROCS |
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| 摘 要： | 支持向量机是在统计学习理论基础上发展起来的一种新的机器学习方法,在模式识别领域有着广泛的应用。利用基于支持向量机模型的31P磁共振波谱数据对肝脏进行分类,区别肝细胞癌,肝硬化和正常的肝组织。通过对基于多项式核函数和径向基核函数的支持向量机分类器进行比较,并且得到三种肝脏分类的识别率。实验表明基于31P磁共振波谱数据的支持向量机分类模型能够对活体肝脏进行诊断性的预测。
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| 关 键 词： | 支持向量机31P 磁共振波谱 肝细胞癌 模式识别 |
~(31)P MRS data diagnosis of hepatocellular carcinoma based on support vector machine |
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| FU Ting-ting,LIU Yi-hui,LIU Qiang,LI Bao-peng,CHENG Jin-yong. ~(31)P MRS data diagnosis of hepatocellular carcinoma based on support vector machine[J]. Chinese Journal of Bioinformatics, 2010, 8(1): 20-22 |
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| Authors: | FU Ting-ting LIU Yi-hui LIU Qiang LI Bao-peng CHENG Jin-yong |
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| Affiliation: | FU Ting-ting1,LIU Yi-hui1,LIU Qiang2,LI Bao-peng2,CHENG Jin-yong1 (1.Institute of Intelligence Information Processing,School of Information Science and Technology,Shandong Institute of Light Industry,Jinan 250353,China,2.Shandong Medical Imaging Research Institute,Jinan 250021,China) |
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| Abstract: | SVM(Support Vector Machine) is a new machine-learning technique which is developed based on statistical theory and has many applications in pattern recognition.We use SVM model based on 31P MRS to distinguish three diagnostic types of hepatocellular carcinoma,hepatic cirrhosis and normal hepatic tissue.The classification accuracy of SVM based on polynomial and radial basis function kernel were compared,and the recognition accuracy of the three categories were obtained.The result of experiments shows that SV... |
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| Keywords: | ~(31)P Support Vector Machine (SVM) ~(31)P (~(31)Phosphorus) Magnetic Resonance Spectroscopy hepatocellular carcinoma pattern recognition |
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