首页> 外文会议>International Conference on Medical Image Computing and Computer-Assisted Intervention(MICCAI 2004) pt.1; 20040926-29; Saint-Malo(FR) >Landmark-Guided Surface Matching and Volumetric Warping for Improved Prostate Biopsy Targeting and Guidance
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Landmark-Guided Surface Matching and Volumetric Warping for Improved Prostate Biopsy Targeting and Guidance

机译:具有里程碑意义的表面匹配和容积扭曲,以改善前列腺活检的靶向性和指导性

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摘要

We present a composite method for landmark-guided surface matching and volumetric non-rigid registration, with an application to prostate biopsy. The two-step method, based primarily on finite element and thin-plate spline techniques, consists of a boundary matching process, followed by a volumetric warping step. In practice, the boundary matching method allows for registration of anatomical surfaces, such as prostate gland capsules, in a way that is bijective, i.e. one-to-one and onto. The novelty of this approach is that it allows for the exact matching of pre-specified corresponding landmark points on the two surfaces to be matched. The second step, volumetric warping, is presented as an extension of our previous work in prostate registration, having been improved to address the problem of non-bijectivity (the "flipping" of tetrahedra) which can result from the linear-elastic modelling of the deformation. We discuss the use of our method for the registration of pre-operative magnetic resonance (MR) imaging for improved targeting and visualization during MR-guided prostate biopsy. Although presented within the context of prostate MR image registration, our composite surface matching and volumetric registration method has general applicability to other organs and imaging modalities such as CT and ultrasound.
机译:我们提出了一种具有里程碑意义的表面匹配和体积非刚性配准的复合方法,并将其应用于前列腺活检。主要基于有限元和薄板样条线技术的两步法包括边界匹配过程,然后是体积弯曲步骤。在实践中,边界匹配方法允许以双射的方式,即一对一地且在其上的方式来配准诸如前列腺腺囊的解剖表面。这种方法的新颖之处在于,它允许将要匹配的两个表面上的预先指定的对应界标点进行精确匹配。第二步,体积翘曲,是对我们先前在前列腺注册中的工作的扩展,已经进行了改进,以解决由双线性模型的线性弹性建模导致的非双性问题(四面体的“翻转”)。形变。我们讨论了使用我们的方法对术前磁共振(MR)成像进行配准,以改善MR引导的前列腺活检过程中的靶向和可视化。尽管是在前列腺MR图像配准的背景下提出的,但我们的复合表面匹配和体积配准方法对其他器官和成像方式(如CT和超声)普遍适用。

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