8907

Practical Patient-Specific Cardiac Blood Flow Simulations Using SPH

Scott Kulp, Mingchen Gao, Shaoting Zhang, Zhen Qian, Szilard Voros, Dimitris Metaxas, Leon Axel
CBIM Center, Rutgers University, Piscataway, NJ 08854, USA
The IEEE International Symposium on Biomedical Imaging (ISBI’13), 2013
@article{kulp2013practical,

   title={PRACTICAL PATIENT-SPECIFIC CARDIAC BLOOD FLOW SIMULATIONS USING SPH},

   author={Kulp, S. and Gao, M. and Zhang, S. and Qian, Z. and Voros, S. and Metaxas, D. and Axel, L.},

   year={2013}

}

Download Download (PDF)   View View   Source Source   

440

views

While recent developments in the field of ventricular blood flow simulations have pushed modeling to increasingly high levels of accuracy, there has been a steep cost in computation time. Current state-of-the-art simulators take days to run, which is impractical for use in a clinical setting. In this paper, we describe novel adaptations of the SPH algorithm to this problem to achieve an order of magnitude faster performance, while maintaining accuracy in the flow. By constructing appropriate boundary particles and wall motion and adding a fast collision detection component to an existing SPH architecture, our system is able to simulate a cardiac cycle in as little as 30 minutes. This breakthrough will, in the near future, allow the useful simulation of blood flow and its related characterization for clinically useful applications.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

166 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1272 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: