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Non-Rigid 2D-3D Registration for Use in Computer-Assisted Abdominal Aortic Aneurysm Repair Procedures

机译:非刚性2D-3D配准,用于计算机辅助腹主动脉瘤修复程序

摘要

This thesis contributes to knowledge by describing three methods to non-rigidly register 2D X-ray images acquired during a Complex Endovascular Aneurysm Repair (CEVAR) procedure to a 3D pre-operative CT scan. The first part of the thesis presents an interpolation framework (thin-plate spline) that is tailored to accurately register 3D CT scan data to 2D X-ray projection data. Registering the 3D to the 2D images proves challenging, due to the lack of information perpendicular to the imaging plane. A method to interpolate manually selected displacements of 3D points located on the aorta surface has been tailored to model the known error distribution along the X-ray projection directions. The second part of the thesis describes the intra-operative use of finite element based algorithms to deform the aorta surface based upon the positions of a guidewire during a CEVAR procedure. The aorta is sequentially deformed so as to encompass a simulated wire which was initialised at the centrelines of the aorta and which is dragged towards the guide-wire. Experiments were conducted on the mechanical parameters of the finite-element model and showed the influence of the Young Modulus and the Poisson’s ratio on registration accuracy. The third part of the thesis focuses on the novel use of interventional digital tomosynthesis images to extract intra-operative information on the calcifications of the aorta and drive non-rigid registration of the aorta during CEVAR. Calciumbased correspondences were established between the pre-operative and the intraoperative scene. A similarity measure has been defined as a weighted sum of a bending energy term and a second term that estimates how well pre-operative and intra-operative patches of calcium match. Erroneous correspondences are corrected using a simulated annealing optimisation on this similarity measure. Using the three methods, large rigid registration errors of 9 mm were brought down to 4 mm or below the clinical target of 3 mm (half the diameter of the renal arteries). The proposed methods fit well with current clinical workflows. The first method presented above requires little manual input during the operation and the two other methods are/can be fully automated. The work presented in this thesis has the potential to increase the availability of image guidance systems for CEVAR procedures and for minimally invasive surgery where soft tissues are involved.
机译:本论文通过描述三种将复杂的血管内动脉瘤修复(CEVAR)程序中获得的2D X射线图像非刚性地注册到3D术前CT扫描中的方法,为知识做出了贡献。论文的第一部分提出了一种插值框架(薄板样条线),该插值框架旨在将3D CT扫描数据准确地注册到2D X射线投影数据中。由于缺乏垂直于成像平面的信息,将3D图像注册到2D图像证明具有挑战性。一种用于插值位于主动脉表面上的3D点的手动选择的位移的方法已经过调整,可以对沿X射线投影方向的已知误差分布进行建模。论文的第二部分描述了术中使用基于有限元的算法在CEVAR手术中根据导丝的位置使主动脉表面变形。主动脉顺序变形,以便包围模拟导线,该模拟导线在主动脉的中心线处初始化并被拖向导丝。对有限元模型的力学参数进行了实验,并显示了杨氏模量和泊松比对套准精度的影响。论文的第三部分着重介绍了介入数字断层合成图像的新颖用法,以提取术中有关主动脉钙化的信息,并在CEVAR期间驱动主动脉的非刚性配准。在术前和术中场景之间建立了基于钙的对应关系。相似性度量已定义为弯曲能量项和第二项的加权总和,该项估计术前和术中钙片的匹配程度。使用模拟退火优化对此相似性度量进行校正,可以纠正错误的对应关系。使用这三种方法,将9 mm的大的刚性套准误差降低到4 mm或低于3 mm的临床目标(肾动脉直径的一半)。提出的方法非常适合当前的临床工作流程。上面介绍的第一种方法在操作过程中几乎不需要人工输入,而其他两种方法则是/可以完全自动化的。本文提出的工作有可能增加用于CEVAR手术和涉及软组织的微创手术的图像引导系统的可用性。

著录项

  • 作者

    Guyot Alexis;

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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