Application of biomechanical modeling techniques in the area of medical image analysis and surgical simulation implies two conflicting requirements: accurate results and high solution speeds. Accurate results can be obtained only by using appropriate models and solution algorithms. In our previous papers we have presented algorithms and solution methods for performing accurate nonlinear finite element analysis of brain shift (which includes mixed mesh, different non-linear material models, finite deformations and brain-skull contacts) in less than a minute on a personal computer for models having up to 50.000 degrees of freedom. In this paper we present an implementation of our algorithms on a Graphics Processing Unit (GPU) using the new NVIDIA Compute Unified Device Architecture (CUDA) which leads to more than 20 times increase in the computation speed. This makes possible the use of meshes with more elements, which better represent the geometry, are easier to generate, and provide more accurate results.

中文翻译：

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GPU 上的实时非线性有限元计算——在神经外科模拟中的应用

生物力学建模技术在医学图像分析和手术模拟领域的应用意味着两个相互矛盾的要求：准确的结果和高求解速度。只有使用合适的模型和求解算法才能获得准确的结果。在我们之前的论文中，我们已经介绍了在不到一分钟的时间内对个人进行精确的大脑移位非线性有限元分析（包括混合网格、不同非线性材料模型、有限变形和脑-颅骨接触）的算法和求解方法。具有高达 50.000 自由度的模型的计算机。在本文中，我们使用新的 NVIDIA 计算统一设备架构 (CUDA) 在图形处理单元 (GPU) 上展示了我们的算法的实现，该架构可将计算速度提高 20 倍以上。这使得使用具有更多元素的网格成为可能，这些网格可以更好地表示几何体、更容易生成并提供更准确的结果。