首页> 外文会议>Conference on developments in X-Ray tomography >Integrated approach to 3D warping and registration from lung images,
【24h】

Integrated approach to 3D warping and registration from lung images,

机译:通过肺部图像进行3D变形和配准的集成方法,

获取原文
获取外文期刊封面目录资料

摘要

Abstract: Computerized volumetric warping and registration of 3D lung images can provide objective, accurate, and reproducible measures to the understanding of human lung structure and function. It is also invaluable to the assessment of the presence of diseases and their response to therapy. However, due to the complexity of breathing motion, little work has been carried out in this research area. In this paper, we propose an integrated approach to implement volumetric lung warping and registration from 3D CT images obtained at different stages of breathing. Both feature points and lung surfaces at consecutive frames are incorporated as a priori knowledge for 3D warping to derive an initial sparse comprehensive displacement field. This comprehensive displacement field is then interpolated over the entire volume in an iterative fashion governed by a model derived from continuum mechanics and 3D optical flow. The iteration is based on an objective function defined by a weighted sum of continuity equation, brightness constraint of 3D optical flow and motion-discontinuity-preserving smoothness constraint. Therefore, the 3D warping is accomplished by minimizing such objective function. This integrated scheme is less sensitive to the distribution of feature points and is resilient to the errors introduced in the process of feature point matching. Preliminary results are visualized by overlaying the displacement field with the original images. Effectiveness of the algorithm is also evaluated according to several checking measures. We believe the proposed approach will open up new areas of research in lung image analysis that can make use of the results from lung volumes warping. !19
机译:摘要:3D肺图像的计算机体积变形和配准可以为了解人的肺结构和功能提供客观,准确和可重现的措施。对于评估疾病的存在及其对治疗的反应,这也是非常宝贵的。然而,由于呼吸运动的复杂性,在该研究领域进行的工作很少。在本文中,我们提出了一种集成的方法,用于从在呼吸的不同阶段获得的3D CT图像实施体积肺翘曲和配准。连续帧中的特征点和肺表面都作为3D翘曲的先验知识而合并,以得出初始的稀疏综合位移场。然后,该综合位移场以迭代方式内插到整个体积上,该迭代方式由从连续力学和3D光流派生的模型控制。迭代基于目标函数,该目标函数由连续性方程的加权和,3D光流的亮度约束和保留运动不连续性的平滑性约束定义。因此,通过使这种目标函数最小化来实现3D变形。该集成方案对特征点的分布不太敏感,并且对在特征点匹配过程中引入的错误具有弹性。通过将位移场与原始图像叠加,可以看到初步结果。还根据几种检查措施来评估算法的有效性。我们相信,所提出的方法将为肺图像分析开辟新的研究领域,从而可以利用肺体积翘曲的结果。 !19

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号