东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2010, Vol. 31 ›› Issue (3): 358-361+365.DOI: -

• 论著 • 上一篇    下一篇

基于灰度共生矩阵和梯度相位互信息的医学图像检索

支力佳;张少敏;赵大哲;赵宏;   

  1. 东北大学信息科学与工程学院;东北大学医学影像计算教育部重点实验室;
  • 收稿日期:2013-06-20 修回日期:2013-06-20 发布日期:2013-06-20
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60671050);;

Medical image retrieval based on gray level co-occurrence matrix and gradient phase mutual information

Zhi, Li-Jia (1); Zhang, Shao-Min (1); Zhao, Da-Zhe (1); Zhao, Hong (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China; (2) The Key Laboratory of Medical Image Computing, Northeastern University, Shenyang 110004, China
  • Received:2013-06-20 Revised:2013-06-20 Published:2013-06-20
  • Contact: Zhi, L.-J.
  • About author:-
  • Supported by:
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摘要： 结合灰度共生矩阵特征和梯度相位互信息,提出了一种面向临床实际应用的两步匹配医学图像检索算法.该算法在提供良好分类性能的灰度共生矩阵特征的基础上,通过精化检索进一步提高了检索精度,以及检索算法的整体鲁棒性.使用该算法对包含有6种不同解剖部位的CT图像库进行检索实验.实验结果表明该算法在达到良好的检索准确性的同时,具有接近实时的查询响应速度.对该算法进行适当扩展,能容易地推广到实际医学检索应用中.

关键词: 基于内容图像检索, 灰度共生矩阵, 梯度相位匹配, 梯度相位互信息

Abstract: A new two-step medical image retrieval algorithm for clinical practice was proposed combining the gray level co-occurrence matrix with gradient phase mutual information. Based on the good classification performance of gray level co-occurrence matrix, the algorithm refines the retrieved process to improve its precision and the integral robustness of the retrieval algorithm. With the algorithm applied to 6 different anatomical positions of CT images, the testing results showed that the algorithm can provide high precision while attaining near real-time speed of response to queries. Expanding properly the algorithm, it can be easily applied to clinical practice in wider fields.

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