南方医科大学学报 ›› 2004, Vol. 24 ›› Issue (05): 579-581.

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CT图像特征的自动获取与检索新方法

周杰, 冯前进, 林亚忠, 陈武凡   

  1. 第一军医大学医学图像处理全军重点实验室, 广东, 广州, 510515
  • 出版日期:2004-05-20 发布日期:2004-05-20
  • 基金资助:
    收稿日期:2003-2-23。
    基金项目:“973”国家重点基础研究发展规划资助项目(2003CB716101);国家自然科学基金重点项目(30130180)
    作者简介:周杰(1972- ),男,第一军医大学在读博士研究生,工程师.电话:020-61648285,E-mail:zhoujie@fimmu.com

Automatic feature extraction and new method for retrieval from CT image database

ZHOU Jie, FENG Qian-jin, LIN Ya-zhong, CHEN Wu-fan   

  1. 第一军医大学医学图像处理全军重点实验室, 广东, 广州, 510515
  • Online:2004-05-20 Published:2004-05-20

摘要: 目的 自动获取CT图像特征,提出实现基于内容的CT图像数据库检索新方法。方法 本研究针对CT医学图像,提出应用最大期望分割算法来获取其区域特征,并组合感兴趣区域的累积直方图特征、纹理和形状信息构成检索的特征向量,从而把图像表征为特征空间中的一个向量集合。结果 当向数据库提交查询图像时,经过特征匹配,最终按相似度由大到小的顺序返回目标图像。结论 实验结果表明,本研究提出的基于内容的CT图像检索方案在满足临床需求的同时,获得了较高的查询精度和效率。

Abstract: Objective To propose a new method for content-based retrieval from medical CT image database on the basis of automatically extracted features of the images. Method An automatic feature extraction method is proposed based on expectation-maximization algorithm. A CT image is represented by a set of regions, each of which is characterized by a fuzzy regional feature vector reflecting the grey level, texture, shape, and the cumulative distribution histogram feature of the region of interest (ROI) to efficiently describe the difference between the ROIs. Results Compared with the submitted query image, the target images were retrieved in the order of similarity calculated by the proposed similarity measures. Conclusion The proposed technique for CT image retrieval is suitable for clinical application, with greater precision and efficiency for retrieval than the conventional methods.

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