计算机应用 ›› 2013, Vol. 33 ›› Issue (09): 2675-2678.DOI: 10.11772/j.issn.1001-9081.2013.09.2675

• 典型应用 • 上一篇    下一篇

三维医学图像配准在图像引导放疗中的应用

吴茜1,2,3,贾婧2,3,曹瑞芬3,裴曦3,吴爱东4,吴宜灿2,3,FDS团队5   

  1. 1. 安徽医科大学 公共基础学院,合肥 230032;
    2. 中国科学技术大学,合肥 230027;
    3. 中国科学院 核能安全技术研究所,合肥 230031;
    4. 安徽省立医院 放疗科,合肥 230001
    5.
  • 收稿日期:2013-03-18 修回日期:2013-05-03 出版日期:2013-09-01 发布日期:2013-10-18
  • 通讯作者: 吴茜
  • 作者简介:吴茜(1985-),女,安徽蚌埠人,讲师,博士研究生,主要研究方向:医学影像配准、医学影像三维重建;
    贾婧(1987-),女,河北石家庄人,博士研究生,主要研究方向:图像引导放射治疗配准、红外引导摆位、放疗中运动控制管理;
    曹瑞芬(1981-),女,河南濮阳人,助理研究员,博士,主要研究方向:精确放疗系统研发;
    裴曦(1984-),男,安徽六安人,助理研究员,博士,主要研究方向:逆向放射治疗系统研发与放疗优化;
    吴爱东(1972-),男,安徽合肥人,高级工程师,博士,主要研究方向:临床肿瘤放疗;
    吴宜灿(1964-),男,安徽安庆人,研究员,博士生导师,博士,主要研究方向:核能科学与工程、辐射医学物理、计算机仿真、软件工程。

Application of three-dimensional medical image registration algorithm in image-guided radiotherapy

WUQian1,2,3,JIA Jing1,3,CAO Ruifen1,PEI Xi1,WU Aidong4,WU Yichan1,3,FDS Team5   

  1. 1. Institute of Nuclear Energy Safety Technology, Chinese Academy of Sciences, Hefei Anhui230031, China;
    2. School of General Education, Anhui Medical University, Hefei Anhui 230032,China;
    3. University of Science and Technology of China, Hefei Anhui 230027, China;
    4. Department of Radiation Oncology, Anhui Provincial Hospital, Hefei Anhui 230001, China
    5.
  • Received:2013-03-18 Revised:2013-05-03 Online:2013-10-18 Published:2013-09-01
  • Contact: WUQian

摘要: 为了确定病人的摆位误差,实现精确放疗,提出一种改进的Demons弹性配准算法。采用FDK算法对锥形束CT(CBCT)图像进行三维重建,利用可视化工具包 (VTK)体绘制法可视化重建结果;在分割与配准工具包 (ITK)基础上实现Demons算法,并基于对称梯度的思想,将参考图像和浮动图像的梯度场信息加入到Demons算法中,给出新的Demons形变力公式。分别使用单模态和多模态医学图像进行配准实验,结果显示改进的Demons算法与原始Demons算法相比,配准速度更快、精度更高。基于对称梯度的Demons算法更适用于图像引导放射治疗中CBCT重建图像与CT计划图像间的配准。

关键词: 图像引导放射治疗, 图像配准, Demons算法, 医学影像, 三维重建, 对称梯度

Abstract: To acquire an accurate patient positioning in image-guided radiotherapy, an improved Demons deformable registration method was developed. The FDK algorithm was adopted to reconstruct Cone Beam CT (CBCT) and the reconstruction result was visualized by a volume rendering method with Visualization ToolKit (VTK). Based on the Insight segmentation and registration ToolKit (ITK), the Demons algorithm was completed incorporating the gradient information of fixed image and floating image by the concept of symmetric gradient, and a new formula of Demons force was demonstrated. Registrion experiments were carried out using medical images both from single modality and multi-modality. The results show that the improved Demons algorithm achieves a faster convergence speed and a higher precision compared with the original demons algorithm, which indicates that the Demons algorithm based on symmetric gradient is more suitable for the registration of CBCT reconstruction image and CT plan image in image-guided radiotherapy.

Key words: image-guided radiotherapy, image registration, Demons algorithm, medical image, three-dimensional reconstruction, symmetric gradient

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