Pose-independent surface matching for intra-operative soft-tissue marker-less registration
Pose-independent surface matching for intra-operative soft-tissue marker-less registration
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DOI：
10.1016/j.media.2014.06.002
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发表时间：
2014-10-01
影响因子：
10.9
通讯作者：
Maier-Hein, Lena
中科院分区：
文献类型：
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作者：
dos Santos, Thiago Ramos;Seitel, Alexander;Maier-Hein, Lena
计算机辅助软组织手术的主要挑战之一是多模态患者特定数据的注册，通过观察暴露的组织表面来增强外科医生的导航能力。一种新的无标记指导方法包括用范围图像设备捕获术中患者解剖结构并进行基于形状的注册。然而，由于目标器官仅部分可见，通常不提供显著特征，并且存在严重的非刚性变形，因此在这种情况下表面匹配极具挑战性。此外，术中获得的表面数据可能受到严重的系统误差和噪声的影响。为了解决这些问题，我们提出了一种建立表面对应关系的新方法，该方法可用于初始化术中基于形状的配准中的精细表面匹配算法。我们的方法不需要任何关于输入表面彼此相对姿态的先验知识，不依赖于突出表面特征的检测，对噪声具有鲁棒性，可用于重叠表面。它考虑了(1)特征描述符的相似性，(2)多个对应对的兼容性，以及(3)整个对应集的空间配置。我们在呼吸肝脏运动模拟器中对猪肝的飞行时间（ToF）数据进行了评估。在我们所有的实验中，根据已建立的表面对应计算的对齐产生的配准误差低于1厘米，因此非常适合于初始化精细表面匹配算法，用于术中软组织配准。(C) 2014 Elsevier B.V.版权所有
One of the main challenges in computer-assisted soft tissue surgery is the registration of multi-modal patient-specific data for enhancing the surgeon's navigation capabilities by observing beyond exposed tissue surfaces. A new approach to marker-less guidance involves capturing the intra-operative patient anatomy with a range image device and doing a shape-based registration. However, as the target organ is only partially visible, typically does not provide salient features and underlies severe non-rigid deformations, surface matching in this context is extremely challenging. Furthermore, the intra-operatively acquired surface data may be subject to severe systematic errors and noise. To address these issues, we propose a new approach to establishing surface correspondences, which can be used to initialize fine surface matching algorithms in the context of intra-operative shape-based registration. Our method does not require any prior knowledge on the relative poses of the input surfaces to each other, does not rely on the detection of prominent surface features, is robust to noise and can be used for overlapping surfaces. It takes into account (1) similarity of feature descriptors, (2) compatibility of multiple correspondence pairs, as well as (3) the spatial configuration of the entire correspondence set. We evaluate the algorithm on time-of-flight (ToF) data from porcine livers in a respiratory liver motion simulator. In all our experiments the alignment computed from the established surface correspondences yields a registration error below I cm and is thus well suited for initializing fine surface matching algorithms for intra-operative soft-tissue registration. (C) 2014 Elsevier B.V. All rights reserved.