图像引导神经外科中脑体积变形的实时生物力学模拟

S. Warfield, M. Ferrant, X. Gallez, A. Nabavi, F. Jolesz, R. Kikinis
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引用次数: 69

摘要

我们的目的是研究术中非刚性配准算法的并行实现性能,该算法可以准确地模拟大脑的生物力学特性及其在手术过程中的变形。该算法旨在改进手术导航和治疗进展的定量监测,以改善手术效果并减少在手术室所需的时间。我们已经将该算法应用于两个神经外科病例,结果令人鼓舞。高性能计算是一项关键的使能技术,它使生物力学模拟能够足够快地执行,使算法具有实用性。我们的并行实现在一个对称多处理器和两个集群上进行了评估,并在每个集群上显示出相似的性能特征。在神经外科手术过程中,这种实现速度足够快,可以在手术室使用。它允许在不到10秒的时间内模拟三维体积变形。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Biomechanical Simulation of Volumetric Brain Deformation for Image Guided Neurosurgery
We aimed to study the performance of a parallel implementation of an intraoperative nonrigid registration algorithm that accurately simulates the biomechanical properties of the brain and its deformations during surgery. The algorithm was designed to allow for improved surgical navigation and quantitative monitoring of treatment progress in order to improve the surgical outcome and to reduce the time required in the operating room. We have applied the algorithm to two neurosurgery cases with promising results. High performance computing is a key enabling technology that allows the biomechanical simulation to be executed quickly enough for the algorithm to be practical. Our parallel implementation was evaluated on a symmetric multi-processor and two clusters and exhibited similar performance characteristics on each. The implementation was sufficiently fast to be used in the operating room during a neurosurgery procedure. It allowed a three-dimensional volumetric deformation to be simulated in less than ten seconds.
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