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新型基于分层多假设跟踪的冠脉骨架提取算法

朱文博 李彬 田联房 陈侃 鲍盈含

朱文博, 李彬, 田联房, 陈侃, 鲍盈含. 新型基于分层多假设跟踪的冠脉骨架提取算法. 自动化学报, 2014, 40(8): 1783-1792. doi: 10.3724/SP.J.1004.2014.01783
引用本文: 朱文博, 李彬, 田联房, 陈侃, 鲍盈含. 新型基于分层多假设跟踪的冠脉骨架提取算法. 自动化学报, 2014, 40(8): 1783-1792. doi: 10.3724/SP.J.1004.2014.01783
ZHU Wen-Bo, LI Bin, TIAN Lian-Fang, CHEN Kan, BAO Ying-Han. A New Coronary Artery Skeleton Extraction Method Based on Layered Multiple Hypothesis Tracking. ACTA AUTOMATICA SINICA, 2014, 40(8): 1783-1792. doi: 10.3724/SP.J.1004.2014.01783
Citation: ZHU Wen-Bo, LI Bin, TIAN Lian-Fang, CHEN Kan, BAO Ying-Han. A New Coronary Artery Skeleton Extraction Method Based on Layered Multiple Hypothesis Tracking. ACTA AUTOMATICA SINICA, 2014, 40(8): 1783-1792. doi: 10.3724/SP.J.1004.2014.01783

新型基于分层多假设跟踪的冠脉骨架提取算法

doi: 10.3724/SP.J.1004.2014.01783
基金项目: 

国家自然科学基金(61305038,61273249),广东省自然科学基金(S2012010009886,S2011010005811),中央高校基本科研业务费重点项目(2013ZZ045),自主系统与网络控制教育部重点实验室资助

详细信息
    作者简介:

    朱文博 华南理工大学自动化科学与工程学院博士研究生.主要研究方向为医学图像处理与模式识别.E-mail:moonkeeper86@126.com

    通讯作者:

    李彬 博士,华南理工大学自动化科学与工程学院副教授.主要研究方向为医学图像处理与模式识别.E-mail:binlee@scut.edu.cn

A New Coronary Artery Skeleton Extraction Method Based on Layered Multiple Hypothesis Tracking

Funds: 

Supported by National Natural Science Foundation of China (61305038, 61273249), Natural Science Foundation of Guangdong Province (S2012010009886, S2011010005811), the Fundamental Research Fund for the Central Universities (2013ZZ045), and The Key Laboratory of Autonomous Systems and Network Control of Ministry of Education

  • 摘要: 为解决大多数脉管骨架提取算法中存在的运算复杂、准确率低以及无法同步获取脉管半径问题,提出了一种新型基于分层多假设跟踪的冠脉骨架提取算法. 首先,提出改进局部形状分析方法用于冠脉预分割,通过引入单连通约束和体积约束和降低非血管型结构及细小类血管型结构误分割率;其次,定义新的中心检测能量函数,增强骨架定位能力,并提出分层多假设策略,避免跟踪过程产生局部最优解和实现脉管半径同步获取;此外,通过生成水平集图,使算法可根据脉管树分支情况自动初始化多条跟踪路径,具有较好的拓扑适应性. 实验表明,与其他骨架提取算法相比,该算法可以同步获取冠脉骨架及半径等信息,且结果精度较高.
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出版历程
  • 收稿日期:  2013-06-27
  • 修回日期:  2014-02-20
  • 刊出日期:  2014-08-20

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