Reichard Daniel, Häntsch Dominik, Bodenstedt Sebastian, Suwelack Stefan, Wagner Martin, Kenngott Hannes, Müller-Stich Beat, Maier-Hein Lena, Dillmann Rüdiger, Speidel Stefanie
Karlsruhe Institute of Technology, Adenauerring 2, Bldg. 50.20, Karlsruhe, Germany.
Department of General, Abdominal and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany.
Int J Comput Assist Radiol Surg. 2017 Jul;12(7):1101-1110. doi: 10.1007/s11548-017-1613-6. Epub 2017 May 26.
A key component of computer- assisted surgery systems is the accurate and robust registration of preoperative planning data with intraoperative sensor data. In laparoscopic surgery, this image-based registration remains challenging due to soft tissue deformations. This paper presents a novel approach for biomechanical soft tissue registration of preoperative CT data with stereo endoscopic image data.
The proposed method consists of two registrations steps. First, we use a 3D surface mosaic from partial surfaces reconstructed from stereo endoscopic images to initially align the biomechanical model with the intraoperative position and shape of the organ. After this initialization, the biomechanical model is projected onto newly captured surfaces, resulting in displacement boundary conditions, which in turn are used to update the biomechanical model.
The method is evaluated in silico, using a human liver model, and in vivo, using porcine data. The quantitative in silico data shows a stable behaviour of the biomechanical model and root-mean-square deviation of volume vertices of under 3 mm with adjusted biomechanical parameters.
This work contributes a fully automatic featureless non-rigid registration approach. The results of the in silico and in vivo experiments suggest that our method is able to handle dynamic deformations during surgery. Additional experiments, especially regarding human tissue behaviour, are an important next step towards clinical applications.
计算机辅助手术系统的一个关键组成部分是术前规划数据与术中传感器数据的准确且稳健的配准。在腹腔镜手术中，由于软组织变形，这种基于图像的配准仍然具有挑战性。本文提出了一种用于术前CT数据与立体内镜图像数据进行生物力学软组织配准的新方法。
所提出的方法包括两个配准步骤。首先，我们使用从立体内镜图像重建的部分表面的三维表面拼接，将生物力学模型与器官的术中位置和形状初步对齐。在这个初始化之后，将生物力学模型投影到新捕获的表面上，从而产生位移边界条件，进而用于更新生物力学模型。
该方法在计算机模拟中使用人体肝脏模型进行评估，并在体内使用猪数据进行评估。计算机模拟的定量数据显示了生物力学模型的稳定行为以及调整生物力学参数后体积顶点的均方根偏差小于3毫米。
这项工作贡献了一种全自动的无特征非刚性配准方法。计算机模拟和体内实验的结果表明，我们的方法能够处理手术过程中的动态变形。额外的实验，特别是关于人体组织行为的实验，是迈向临床应用的重要下一步。
