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CTA影像头部骨骼组织提取算法

曹春红 艾亮 许光星

曹春红, 艾亮, 许光星等 . CTA影像头部骨骼组织提取算法[J]. 北京航空航天大学学报, 2015, 41(6): 982-988. doi: 10.13700/j.bh.1001-5965.2014.0502
引用本文: 曹春红, 艾亮, 许光星等 . CTA影像头部骨骼组织提取算法[J]. 北京航空航天大学学报, 2015, 41(6): 982-988. doi: 10.13700/j.bh.1001-5965.2014.0502
CAO Chunhong, AI Liang, XU Guangxinget al. Head bone tissue extraction algorithm based on CTA image[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(6): 982-988. doi: 10.13700/j.bh.1001-5965.2014.0502(in Chinese)
Citation: CAO Chunhong, AI Liang, XU Guangxinget al. Head bone tissue extraction algorithm based on CTA image[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(6): 982-988. doi: 10.13700/j.bh.1001-5965.2014.0502(in Chinese)

CTA影像头部骨骼组织提取算法

doi: 10.13700/j.bh.1001-5965.2014.0502
基金项目: 国家自然科学基金(61300096); 中央高校基本科研业务费专项资金(N130404013)
详细信息
    通讯作者:

    曹春红(1976—),女,吉林四平人,副教授,caochunhong@ise.neu.edu.cn,主要研究方向为计算机图形学、计算机图像处理.

  • 中图分类号: TP391

Head bone tissue extraction algorithm based on CTA image

  • 摘要: 计算机断层血管造影(CTA)影像单纯根据灰度信息无法良好地分离血管组织和骨骼组织.结合CTA影像的灰度特点,提出基于改进的三维区域生长算法的骨骼组织外轮廓提取和基于改进的Snake模型的骨骼提取算法.首先结合概率论的相关知识改进区域生长判定条件的准确性,提出三维区域生长的快速的骨骼区域种子点提取方法,使得它可以获得比较准确的骨骼组织区域.之后选取Snake模型并对其进行改进,增加了影像能量信息项,使得该模型可以更好地解决当前的问题.最后给出了实验结果并和传统算法进行对比,证实所提出的骨骼组织分割提取算法效果良好.

     

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出版历程
  • 收稿日期:  2014-08-11
  • 网络出版日期:  2015-06-20

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