Compressed sensing MRI with multi-channel data using multi-core processors

Ching Hua Chang, Jim Ji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Compressed sensing (CS) has emerged as a promising method in the field of magnetic resonance imaging. Taking advantage of the signal sparsity in certain domain via L1 minimization, CS requires only reduced k-space data to reconstruct an image. Since most clinical MRI scanners are equipped with multi-channel receiver systems, integrating CS with multi-channel systems may not only shorten the scan time but provide a better image quality. However, significant computation time is required to perform CS reconstruction. Furthermore, this burden will be scaled by the number of channels. In this paper, we proposed a reconstruction procedure, which uses multi-core processors to accelerate CS reconstruction from multiple channel data. The performance was tested in terms of comparing to different image sizes and using different number cores of CPU. Experimentally, it shows that the maximum efficiency benefits from parallelizing the CS reconstructions, pipelining multi-channel data on multi-core processors and choosing the numbers of channels as multiple numbers of cores.

Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Pages2684-2687
Number of pages4
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: 2 Sep 20096 Sep 2009

Other

Other31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
CountryUnited States
CityMinneapolis, MN
Period2/9/096/9/09

Fingerprint

Compressed sensing
Magnetic resonance imaging
Magnetic Resonance Imaging
Magnetic resonance
Image quality
Program processors
Imaging techniques

Keywords

  • Compressed sensing
  • Image reconstruction
  • Multi-channel phased array
  • Multi-core processors

ASJC Scopus subject areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)

Cite this

Chang, C. H., & Ji, J. (2009). Compressed sensing MRI with multi-channel data using multi-core processors. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 2684-2687). [5334095] https://doi.org/10.1109/IEMBS.2009.5334095

Compressed sensing MRI with multi-channel data using multi-core processors. / Chang, Ching Hua; Ji, Jim.

Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. p. 2684-2687 5334095.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chang, CH & Ji, J 2009, Compressed sensing MRI with multi-channel data using multi-core processors. in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009., 5334095, pp. 2684-2687, 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009, Minneapolis, MN, United States, 2/9/09. https://doi.org/10.1109/IEMBS.2009.5334095
Chang CH, Ji J. Compressed sensing MRI with multi-channel data using multi-core processors. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. p. 2684-2687. 5334095 https://doi.org/10.1109/IEMBS.2009.5334095
Chang, Ching Hua ; Ji, Jim. / Compressed sensing MRI with multi-channel data using multi-core processors. Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. pp. 2684-2687
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