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| 基于支持向量机的骨肉瘤X线图像中病变区域的自动识别研究 | |
| 引用本文： | 李超峰,刘燕,胡珊等.基于支持向量机的骨肉瘤X线图像中病变区域的自动识别研究[J].医学信息学杂志,2010,31(9):32-34. |
| 作者姓名： | 李超峰 刘燕 胡珊等 |
| 作者单位： | 1. 中山大学附属肿瘤医院,信息科,广州,510080 2. 中山大学基础医学院生物医学工程系,广州,510080 3. 中山大学附属肿瘤医院信息科,广州,510080 |
| 摘 要： | 采用骨肉瘤X线图像中病变区域的颜色特征和基于灰度共生矩阵的纹理特征作为特征向量,研究利用支持向量机算法对骨肉瘤病变区域的自动识别方法,结果充分表明支持向量机良好的分类能力. |
| 关 键 词： | 支持向量机 灰度共生矩阵 骨肉瘤 自动识别 |
| 收稿时间： | 3/1/2010 12:00:00 AM |
Research on Automatic Recognition of Lesion Areas of Osteosarcoma X-ray Images Based on Support Vector Machine |
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| LI Chao-feng,LIU Yan,HU Shan etal.Research on Automatic Recognition of Lesion Areas of Osteosarcoma X-ray Images Based on Support Vector Machine[J].Journal of Medical Informatics,2010,31(9):32-34. | |
| Authors: | LI Chao-feng LIU Yan HU Shan etal |
| Abstract: | Adopting colour characteristics and texture features based on gray level co-occurrence matrix in lesion areas of osteosarcoma x-ray images as the eigenvector,the paper mainly studies automatic identification method of osteosarcoma lesion areas by using support vector machine algorithm, the result proves that support vector machine has good classification ability. |
| Keywords: | Support vector machine Gray symbiotic matrix Osteosarcoma Automatic recognition |
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