Publication detail

Using GPGPU in MR Data Processing

MIKULKA, J. SLIŽ, J. BARTUŠEK, K.

Original Title

Using GPGPU in MR Data Processing

English Title

Using GPGPU in MR Data Processing

Type

conference paper

Language

en

Original Abstract

The main tissue parameters targeted by MR tomography include, among others, relaxation times T1 and T2. This paper focuses on the computation of the relaxation time T2 measured with the Spin Echo method. The maxima of measured echoes must be interleaved with an exponential function to compute the T2 relaxation. As this procedure needs to be repeated for each pixel of the scanned tissue, the processing of large images then becomes very intensive. This paper introduces the results provided by accelerated computation based on parallelization and carried out with a graphics card. By using the simple method of linear regression, we obtain a processing time of less than 36 ms. In the case of the Levenberg-Marquardt algorithm, the reconstruction was done in 96 ms. This period is at least 900 times shorter than that achievable with professional software.

English abstract

The main tissue parameters targeted by MR tomography include, among others, relaxation times T1 and T2. This paper focuses on the computation of the relaxation time T2 measured with the Spin Echo method. The maxima of measured echoes must be interleaved with an exponential function to compute the T2 relaxation. As this procedure needs to be repeated for each pixel of the scanned tissue, the processing of large images then becomes very intensive. This paper introduces the results provided by accelerated computation based on parallelization and carried out with a graphics card. By using the simple method of linear regression, we obtain a processing time of less than 36 ms. In the case of the Levenberg-Marquardt algorithm, the reconstruction was done in 96 ms. This period is at least 900 times shorter than that achievable with professional software.

Keywords

GPGPU, image processing, T2 relaxation, spin echo, interpolation

Released

12.09.2016

Publisher

VUT FEKT UTEE

Location

Brno

ISBN

9788021453876

Book

International Interdisciplinary PhD Workshop 2016 Proceedings

Pages from

102

Pages to

106

Pages count

5

URL

Documents

BibTex


@inproceedings{BUT127764,
  author="Jan {Mikulka} and Jiří {Sliž} and Karel {Bartušek}",
  title="Using GPGPU in MR Data Processing",
  annote="The main tissue parameters targeted by MR tomography include, among others, relaxation times T1 and T2. This paper focuses on the computation of the relaxation time T2 measured with the Spin Echo method. The maxima of measured echoes must be interleaved with an exponential function to compute the T2 relaxation. As this procedure needs to be repeated for each pixel of the scanned tissue, the processing of large images then becomes very intensive. This paper introduces the results provided by accelerated computation based on parallelization and carried out with a graphics card. By using the simple method of linear regression, we obtain a processing time of less than 36 ms. In the case of the Levenberg-Marquardt algorithm, the reconstruction was done in 96 ms. This period is at least 900 times shorter than that achievable with professional software.",
  address="VUT FEKT UTEE",
  booktitle="International Interdisciplinary PhD Workshop 2016 Proceedings",
  chapter="127764",
  howpublished="electronic, physical medium",
  institution="VUT FEKT UTEE",
  year="2016",
  month="september",
  pages="102--106",
  publisher="VUT FEKT UTEE",
  type="conference paper"
}