Current-and Varifold-Based Registration of Lung Vessel and Airway Trees

Current-and Varifold-Based Registration of Lung Vessel and Airway Trees
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基于电流和多样性的肺血管和气道树配准

DOI:
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发表时间:
2016
期刊:
2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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通讯作者:
Geoffrey D. Hugo
Geoffrey D. Hugo
中科院分区:
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文献类型:
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作者:
Yue Pan;G. Christensen;O. Durumeric;S. Gerard;J. Reinhardt;Geoffrey D. Hugo

文献摘要

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配准肺部 CT 图像对于许多应用来说都是一个重要问题,包括跟踪呼吸周期中的肺部运动、跟踪解剖和功能随时间的变化以及检测肺部的异常机械特性。本文比较和对比了当前和基于多种的微分同胚图像配准方法,用于配准肺部的树状结构。在这些方法中,肺部的曲线状结构(例如,血管和气道分割的骨架)由再生核希尔伯特空间(RKHS)的对偶空间中的电流或曲折表示。当前和多种表示被离散化,并通过动量集合进行参数化。动量通过线段中心的坐标和线段在中心的切线方向对应于线段。基于多样性的配准方法与当前的方法类似,不同之处在于两个多样性表示的对齐与切向量方向无关。与电流相比,varifold 的优点是切向量的方向可能难以确定,特别是当血管和气道树未连接时。在本文中,我们检查了基于电流和基于多样性的配准的图像配准灵敏度和准确性,作为用于表示肺部树状结构的动量的数量和位置的函数。本文中提出的配准是使用 Deformetrica 软件包生成的([Durrleman et al. 2014])。
Registering lung CT images is an important problem for many applications including tracking lung motion over the breathing cycle, tracking anatomical and function changes over time, and detecting abnormal mechanical properties of the lung. This paper compares and contrasts current-and varifold-based diffeomorphic image registration approaches for registering tree-like structures of the lung. In these approaches, curve-like structures in the lung—for example, the skeletons of vessels and airways segmentation—are represented by currents or varifolds in the dual space of a Reproducing Kernel Hilbert Space (RKHS). Current and varifold representations are discretized and are parameterized via of a collection of momenta. A momenta corresponds to a line segment via the coordinates of the center of the line segment and the tangent direction of the line segment at the center. A varifold-based registration approach is similar to currents except that two varifold representations are aligned independent of the tangent vector orientation. An advantage of varifolds over currents is that the orientation of the tangent vectors can be difficult to determine especially when the vessel and airway trees are not connected. In this paper, we examine the image registration sensitivity and accuracy of current-and varifold-based registration as a function of the number and location of momentum used to represent tree like-structures in the lung. The registrations presented in this paper were generated using the Deformetrica software package ([Durrleman et al. 2014]).