Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (9): 208-211.DOI: 10.3778/j.issn.1002-8331.2010.09.059

• 工程与应用 • Previous Articles     Next Articles

Research on clear redundancy in brain CT images

SONG Liang,GENG Guo-hua   

  1. College of Information Science and Technology,Northwest University,Xi’an 710127,China
  • Received:2008-09-22 Revised:2008-11-27 Online:2010-03-21 Published:2010-03-21
  • Contact: SONG Liang


宋 亮,耿国华   

  1. 西北大学 信息科学与技术学院,西安 710127
  • 通讯作者: 宋 亮

Abstract: Brain CT images always have some redundancy such as metal slots,clothes and shoulders.This paper divides the redundancy into two kinds based on its distribution and proposes a new algorithm which combines the FCM and contour track to clear redundancy in CT images.The algorithm solves the problem of the lost of CT data in traditional method.The algorithm can automatically deal with a batch of CT data and it is proved to have good effect and some apply value through experiments.

Key words: Computed Tomography(CT) image, fuzzy-C means clustering, contour track, 3D model reconstruction

摘要: 脑部CT图像中通常存在金属槽,衣物以及肩膀组织等类似的冗余影像数据,根据冗余数据的分布特点将其分为两种类型,提出了一种新的结合模糊C均值以及轮廓跟踪方法的去除CT图像中冗余影像数据的算法,该算法解决了以往算法中出现的CT数据的丢失问题。算法可以实现对大量CT数据的自动批处理,实验证明算法效果良好并且具有一定的实用价值。

关键词: CT图像, 模糊C均值, 轮廓跟踪, 三维模型重建

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