计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (34): 222-224.DOI: 10.3778/j.issn.1002-8331.2009.34.069

• 工程与应用 • 上一篇    下一篇

一种新的肝肿瘤CT图像分割方法

陈灵娜,罗 扬,陈增科   

  1. 南华大学 计算机学院,湖南 衡阳 421001
  • 收稿日期:2008-07-04 修回日期:2008-10-06 出版日期:2009-12-01 发布日期:2009-12-01
  • 通讯作者: 陈灵娜

New method on liver tumor CT image segmentation

CHEN Ling-na,LUO Yang,CHEN Zeng-ke   

  1. Department of Computer Science and Technology,University of South China,Hengyang,Hunan 421001,China
  • Received:2008-07-04 Revised:2008-10-06 Online:2009-12-01 Published:2009-12-01
  • Contact: CHEN Ling-na

摘要: 传统的分割方法难以实现医学图像准确地分割,提出了基于最大信息熵原理的医学图像分割方法。该方法集成了阈值分割、边界跟踪和数学形态学,提高了分割的精度和速度。分析和实验结果表明,采用该方法对肝肿瘤CT图像进行分割时,能自动准确地提取出医生感兴趣的区域。

Abstract: Traditional segmentation methods can not realize true medical image segmentation,therefore a new approach of medical image segmentation based on principle of maximum entropy is presented in this paper.The method uses threshold segmentation,boundary tracking and mathematical morphology in a comprehensive way,and it improves the speed and accuracy of segmentation.Analysis and experiment prove that this method can extract Regions Of Interest(ROI) in the liver tumor CT images.

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