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计算机辅助诊断中的肿瘤形状特征分类
CLASSIFICATION OF TUMOR SHAPE IN COMPUTER-AIDED DIAGNOSIS
【摘要】 为了克服传统的蛇形算法不能收敛于边缘凹陷处以及对蛇的初始化过于敏感的缺点,本文提出用基于可变形模型的梯度矢量流方法提取乳腺X光片中的肿瘤区域。在此基础上,提出三个新的基于边缘的价矩,和其它肿瘤的形状特征作为改进的支持向量机分类法的特征输入,进行恶性肿瘤和良性肿瘤的计算机辅助诊断,取得了良好效果。
【Abstract】 In order to overcome the problems of traditional snake associated with poor convergence to boundary concavities and sensitive initialization,gradient vector flow based on deformable models is presented to segment tumor region.And three new moments based on boundary are also developed.Apart from those,the novel support vector machine classifier applies other shape features to classify the tumor into the malignant or the benign.The proposed computer-aided diagnose system achieves good result.
【关键词】 可变形模型;
梯度矢量流;
肿瘤;
形状特征;
支撑向量机;
【Key words】 Deformable model Gradient vector flow Tumor Shape features Support vector machine;
【Key words】 Deformable model Gradient vector flow Tumor Shape features Support vector machine;
【基金】 自然科学基金项目(No60372072)资助
- 【文献出处】 计算机应用与软件 ,Computer Applications and Software , 编辑部邮箱 ,2006年02期
- 【分类号】TP399
- 【被引频次】7
- 【下载频次】252