| 基于增强关联规则的医学图像分类新方法 |
| |
| 引用本文： | 蒋芸,李战怀,王勇,张龙波.基于增强关联规则的医学图像分类新方法[J].西北工业大学学报,2006,24(3):401-404. |
| |
| 作者姓名： | 蒋芸 李战怀 王勇 张龙波 |
| |
| 作者单位： | 西北工业大学,计算机学院,陕西,西安,710072 |
| |
| 基金项目： | 国家自然科学基金(60373108、60573096)资助 |
| |
| 摘 要： | 由于乳腺X光图像的复杂性,直接从图像中看出肿瘤及其良、恶性质是很困难的,因此建立高效的肿瘤自动诊断系统非常必要。文中将关联规则分类器和粗糙集理论相结合构造了增强关联规则分类器(EAC),应用于乳腺X光图像分类。实验结果表明,EAC的分类精确度可达到77.48%,比单独使用关联规则的分类精确度(69.11%)要高近10%,同时规则数也明显减少。
|
| 关 键 词： | 增强关联规则分类器 粗糙集理论 乳腺X光图像 |
| 文章编号： | 1000-2758(2006)03-401-04 |
| 收稿时间： | 2005-09-06 |
| 修稿时间： | 2005年9月6日 |
A Better Classifier Based on Data Mining for Mammographic Images |
| |
| Jiang Yun,Li Zhanhuai,Wang Yong,Zhang Longbo.A Better Classifier Based on Data Mining for Mammographic Images[J].Journal of Northwestern Polytechnical University,2006,24(3):401-404. |
| |
| Authors: | Jiang Yun Li Zhanhuai Wang Yong Zhang Longbo |
| |
| Abstract: | Purpose.There exist only several methods based on data mining for classifying mammographic images~().We present a new method,also based on data mining,that we believe is better than existing ones.In the full paper,we explain our new method in detail;in this abstract,we just list the two topics of our explanation:(1) pretreating images and extracting their features;(2) enhanced associative classifier(EAC),whose subtopics are rough sets theory,associative rule,and algorithm for EAC.The experimental results,given in detail in Table 1 in the full paper,show that this EAC can get 77.48% classification accuracy which is higher than the 69.11% obtained by Ref.1 with associative classifier;furthermore the number of rules is much fewer than that of Ref.1. |
| |
| Keywords: | enhanced associative classifier(EAC) rough sets theory mammographic image |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
