Vigneron Lara M, Warfield Simon K, Robe Pierre A, Verly Jacques G
Department of Electrical Engineering and Computer Science, University of Liège, Liège, Belgium.
Comput Aided Surg. 2011;16(3):121-34. doi: 10.3109/10929088.2011.570090.
Outcomes for neurosurgery patients can be improved by enhancing intraoperative navigation and guidance. Current navigation systems do not accurately account for intraoperative brain deformation. So far, most studies of brain deformation have focused on brain shift, whereas this paper focuses on the brain deformation due to retraction. The heart of our system is a 3D nonrigid registration technique using a biomechanical model driven by the deformations of key surfaces tracked between two intraoperative images. The key surfaces, e.g., the whole-brain region boundary and the lips of the retraction cut, thus deform due to the combination of gravity and retractor deployment. The tissue discontinuity due to retraction is handled via the eXtended Finite Element Method (XFEM), which has the appealing feature of being able to handle arbitrarily shaped discontinuity without any remeshing. Our approach is shown to significantly improve the alignment of intraoperative MRI.
通过增强术中导航和引导可以改善神经外科手术患者的治疗效果。当前的导航系统不能准确地考虑术中脑形变。到目前为止，大多数关于脑形变的研究都集中在脑移位上，而本文关注的是由于脑牵拉引起的脑形变。我们系统的核心是一种三维非刚性配准技术，它使用一个生物力学模型，该模型由在两个术中图像之间跟踪的关键表面的形变驱动。关键表面，例如全脑区域边界和牵拉切口边缘，会由于重力和牵开器展开的共同作用而发生形变。由于牵拉导致的组织不连续性通过扩展有限元方法（XFEM）来处理，该方法具有能够处理任意形状的不连续性而无需任何重新网格化的吸引人的特性。我们的方法被证明能显著改善术中MRI的配准。
