...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of computer sciences >CONTENT BASED MEDICAL IMAGE RETRIEVAL USING BINARY ASSOCIATION RULES | Science Publications
【24h】

CONTENT BASED MEDICAL IMAGE RETRIEVAL USING BINARY ASSOCIATION RULES | Science Publications

机译：二元关联规则的基于内容的医学图像检索科学出版物

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

> In this study, we propose a content-based medical image retrieval framework based on binary association rules to augment the results of medical image diagnosis, for supporting clinical decision making. Specifically, this work is employed on scanned Magnetic Resonance brain Images (MRI) and the proposed Content Based Image Retrieval (CBIR) process is for enhancing relevancy rate of retrieved images. The pertinent features of a query brain image are extracted by applying third order moment invariant functions, which are then examined with the selected feature indexes of large medical image database for appropriate image retrieval. Binary association rules are incorporated here for organizing and marking the significant features of database images, regarding a specific criterion. Trigonometric function distance similarity measurement algorithm is applied to improve the accuracy rate of results. Moreover, the performances of classification and retrieval methods are determined in terms of precision and recall rates. Experimental results reveal the efficacy of the adduced methodology as compared to the related works.
机译： >在本研究中，我们提出了一种基于二进制关联规则的基于内容的医学图像检索框架，以增强医学图像诊断的结果，以支持临床决策。具体而言，这项工作是在扫描的磁共振脑图像（MRI）上进行的，所提出的基于内容的图像检索（CBIR）过程用于提高检索图像的相关率。通过应用三阶矩不变函数来提取查询大脑图像的相关特征，然后使用大型医学图像数据库的选定特征索引对其进行检查以进行适当的图像检索。此处结合了二进制关联规则，用于针对特定标准组织和标记数据库图像的重要功能。应用三角函数距离相似度测量算法提高了结果的准确率。此外，分类和检索方法的性能取决于准确性和查全率。实验结果表明，与相关工作相比，上述方法的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号