Vigneron Lara M, Noels Ludovic, Warfield Simon K, Verly Jacques G, Robe Pierre A
Department of Electrical Engineering and Computer Science, University of Liège, 4000 Liège, Belgium.
Int J Biomed Imaging. 2012;2012:872783. doi: 10.1155/2012/872783. Epub 2012 Jan 12.
Current neuronavigation systems cannot adapt to changing intraoperative conditions over time. To overcome this limitation, we present an experimental end-to-end system capable of updating 3D preoperative images in the presence of brain shift and successive resections. The heart of our system is a nonrigid registration technique using a biomechanical model, driven by the deformations of key surfaces tracked in successive intraoperative images. The biomechanical model is deformed using FEM or XFEM, depending on the type of deformation under consideration, namely, brain shift or resection. We describe the operation of our system on two patient cases, each comprising five intraoperative MR images, and we demonstrate that our approach significantly improves the alignment of nonrigidly registered images.
当前的神经导航系统无法随时间适应术中不断变化的情况。为克服这一局限性，我们提出了一种实验性的端到端系统，该系统能够在存在脑移位和连续切除的情况下更新术前三维图像。我们系统的核心是一种使用生物力学模型的非刚性配准技术，该模型由在连续术中图像中跟踪的关键表面变形驱动。根据所考虑的变形类型（即脑移位或切除），使用有限元法（FEM）或扩展有限元法（XFEM）使生物力学模型变形。我们描述了我们的系统在两个患者病例上的操作，每个病例包含五张术中磁共振图像，并证明我们的方法显著改善了非刚性配准图像的对齐。
