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Registration of Tomographic Images to X-ray Projections for Use in Image Guided Interventions

机译:将层析图像注册到X射线投影中,以用于图像引导干预

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摘要

This thesis contributes to knowledge by describing a new method to allowinformation from a pre-operative 3D modality to be used during an intervention which is guided using 2D fluoroscopy images. An algorithm has been designed to obtain the pose of a CT volume with respect to a single fluoroscopy image. The registration algorithm is based on the production of digitally reconstructed radiographs from the CT volume, which are compared to the fluoroscopy image using a similarity measure.The novelty of the work described in this thesis is in both the design ofthe registration algorithm and also in investigating the specific requirements placed upon a similarity measure when attempting to register a pre-operative CT volume to an interventional fluoroscopy image. Seven similarity measures were investigated. Experiments were carried out to calculate the accuracy and robustness of the registration algorithm using each similarity measure. Initially fluoroscopy and CT images of a lumbar spine phantom were used. The accuracy of the registration algorithm was calculated by comparing the final registration positions with a ``gold-standard'' registration calculated using fiducial markers. More realistic datasets were simulated using the phantom fluoroscopy image with clinical image features overlaid. Results show that the introduction of soft-tissue structures and interventional instruments into the phantom image can have a large effect on the performance of some similarity measures previously applied to 2D-3D image registration. The similarity measures were also tested on clinicaldata from aortic stenting procedures, where k-fold cross validation wasused to obtain an estimate of the registration accuracy. The results from these experiments showed that two measures were able toregister accurately (RMS rotational error of 0.76 degrees and RMS in-plane translational error of 0.85mm) and robustly (10% failure rate) even when soft-tissue structures and interventional instruments were present as differences between the images. These two measures were pattern intensity and gradient difference. Finally the thesis describes a novel combination of the 2D-3D registrationalgorithm with a deformation algorithm. The registration algorithm was usedto obtain information on the relative movement of the vertebrae betweenthe pre-operative CT image and interventional fluoroscopy image. Thisinformation was then used to warp the pre-operative modality so that it moreaccurately represented the intra-operative scene.
机译:本论文通过描述一种新的方法来为知识做出贡献,该方法允许使用术前3D模态提供的信息,以2D透视图像为指导进行干预。设计了一种算法来获得相对于单个透视图像的CT体积的姿态。配准算法是基于从CT体积生成数字重建的X射线照片,然后使用相似性度量将其与透视图像进行比较。本文描述的工作新颖之处在于配准算法的设计以及研究尝试将术前CT体积记录到介入性透视图像上时,对相似性度量的具体要求。研究了七个相似性度量。进行了实验,以使用每种相似性度量来计算配准算法的准确性和鲁棒性。最初使用的是腰椎幻影的荧光检查和CT图像。通过将最终注册位置与使用基准标记计算出的``黄金标准''注册进行比较,计算出注册算法的准确性。使用幻影透视图像叠加了临床图像特征,可以模拟更逼真的数据集。结果表明,在幻影图像中引入软组织结构和介入器械可能会对以前应用于2D-3D图像配准的某些相似性度量的性能产生重大影响。还对来自主动脉支架置入术的临床数据进行了相似性测试,其中使用了k倍交叉验证来获得对套准准确性的估计。这些实验的结果表明,即使存在软组织结构和介入器械,两种措施也能够准确记录(RMS旋转误差为0.76度,RMS平面内平移误差为0.85mm)和鲁棒性(失败率10%)。作为图像之间的差异。这两个量度是图案强度和梯度差。最后,论文描述了二维3D配准算法与变形算法的新型结合。配准算法用于获得有关术前CT图像和介入性透视图像之间的椎骨相对运动的信息。然后,此信息将用于扭曲术前模式,以便更准确地表示术中场景。

著录项

  • 作者

    Penney Graeme;

  • 作者单位
  • 年度 2000
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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