Detail publikace

Electrical Impedance Tomography Methods and Algorithms Processed with a GPU

DUŠEK, J. HLADKÝ, D. MIKULKA, J.

Originální název

Electrical Impedance Tomography Methods and Algorithms Processed with a GPU

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The present paper discusses the process of parallelizing an algorithm for the reconstruction of an image acquired via electrical impedance tomography (EIT). The introductory section comprises a general description of EIT, the inverse problem, and regularization; in this context, the potential of the method for biomedicine, defectoscopy, and geophysical mapping is outlined. The following chapter then analyzes the objective function of the EIT inverse problem together with Tikhonov regularization. Besides setting up the objective function with a regularizing member, the authors also specify the differentiation equation for the iterative solution of the inverse problem via the Gauss-Newton method. Further, the time consumption of computing the Jacobian via a CPU compared to using a newly assembled program that exploits GPU-based parallel processing is investigated in detail. The program, utilizing the NVIDIA CUDA platform, employs parallelized computation of the individual columns of the Jacobi matrix, and this approach proved to be twenty times faster than the CPU-based sequential processing.

Klíčová slova

Electrical impedance tomography; image reconstruction; Tikhonov regularization; objective function; parallelization

Autoři

DUŠEK, J.; HLADKÝ, D.; MIKULKA, J.

Vydáno

24. 5. 2017

ISBN

978-1-5090-6269-0

Kniha

PIERS Proceedings (Spring) 2017

Strany od

1710

Strany do

1714

Strany počet

5

URL

https://ieeexplore.ieee.org/document/8262025

BibTex

@inproceedings{BUT137881,
  author="Jan {Dušek} and David {Hladký} and Jan {Mikulka}",
  title="Electrical Impedance Tomography Methods and Algorithms Processed with a GPU",
  booktitle="PIERS Proceedings (Spring) 2017",
  year="2017",
  pages="1710--1714",
  doi="10.1109/PIERS.2017.8262025",
  isbn="978-1-5090-6269-0",
  url="https://ieeexplore.ieee.org/document/8262025"
}