4.7 Article

Real-time nonlinear finite element computations on GPU - Application to neurosurgical simulation

Journal

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
Volume 199, Issue 49-52, Pages 3305-3314

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2010.06.037

Keywords

Non-rigid image registration; Biomechanical models; Dynamic relaxation; Graphics processing unit; CUDA

Funding

  1. Australian Research Council [DP0664534, DP0770275, LX0774754]
  2. University of Western Australia
  3. National Institute of Health [R03 CA126466]
  4. NATIONAL CANCER INSTITUTE [R03CA126466] Funding Source: NIH RePORTER
  5. NATIONAL CENTER FOR RESEARCH RESOURCES [R01RR021885] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [R01EB008015] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM074068] Funding Source: NIH RePORTER

Ask authors/readers for more resources

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. (C) 2010 Elsevier B.V. All rights reserved.

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