Accelerated cardiac diffusion tensor imaging using joint low-rank and sparsity constraints

Sen Ma, Christopher T. Nguyen, Anthony G. Christodoulou, Daniel Luthringer, Jon Kobashigawa, Sang Eun Lee, Hyuk-Jae Chang, Debiao Li

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Objective: The purpose of this paper is to accelerate cardiac diffusion tensor imaging (CDTI) by integrating low-rankness and compressed sensing. Methods: Diffusion-weighted images exhibit both transform sparsity and low-rankness. These properties can jointly be exploited to accelerate CDTI, especially when a phase map is applied to correct for the phase inconsistency across diffusion directions, thereby enhancing low-rankness. The proposed method is evaluated both ex vivo and in vivo, and is compared to methods using either a low-rank or sparsity constraint alone. Results: Compared to using a low-rank or sparsity constraint alone, the proposed method preserves more accurate helix angle features, the transmural continuum across the myocardium wall, and mean diffusivity at higher acceleration, while yielding significantly lower bias and higher intraclass correlation coefficient. Conclusion: Low-rankness and compressed sensing together facilitate acceleration for both ex vivo and in vivo CDTI, improving reconstruction accuracy compared to employing either constraint alone. Significance: Compared to previous methods for accelerating CDTI, the proposed method has the potential to reach higher acceleration while preserving myofiber architecture features, which may allow more spatial coverage, higher spatial resolution, and shorter temporal footprint in the future.

Original languageEnglish
Article number8239837
Pages (from-to)2219-2230
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Volume65
Issue number10
DOIs
Publication statusPublished - 2018 Oct 1

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Diffusion tensor imaging
Compressed sensing

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Cite this

Ma, S., Nguyen, C. T., Christodoulou, A. G., Luthringer, D., Kobashigawa, J., Lee, S. E., ... Li, D. (2018). Accelerated cardiac diffusion tensor imaging using joint low-rank and sparsity constraints. IEEE Transactions on Biomedical Engineering, 65(10), 2219-2230. [8239837]. https://doi.org/10.1109/TBME.2017.2787111
Ma, Sen ; Nguyen, Christopher T. ; Christodoulou, Anthony G. ; Luthringer, Daniel ; Kobashigawa, Jon ; Lee, Sang Eun ; Chang, Hyuk-Jae ; Li, Debiao. / Accelerated cardiac diffusion tensor imaging using joint low-rank and sparsity constraints. In: IEEE Transactions on Biomedical Engineering. 2018 ; Vol. 65, No. 10. pp. 2219-2230.
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Ma, S, Nguyen, CT, Christodoulou, AG, Luthringer, D, Kobashigawa, J, Lee, SE, Chang, H-J & Li, D 2018, 'Accelerated cardiac diffusion tensor imaging using joint low-rank and sparsity constraints', IEEE Transactions on Biomedical Engineering, vol. 65, no. 10, 8239837, pp. 2219-2230. https://doi.org/10.1109/TBME.2017.2787111

Accelerated cardiac diffusion tensor imaging using joint low-rank and sparsity constraints. / Ma, Sen; Nguyen, Christopher T.; Christodoulou, Anthony G.; Luthringer, Daniel; Kobashigawa, Jon; Lee, Sang Eun; Chang, Hyuk-Jae; Li, Debiao.

In: IEEE Transactions on Biomedical Engineering, Vol. 65, No. 10, 8239837, 01.10.2018, p. 2219-2230.

Research output: Contribution to journalArticle

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N2 - Objective: The purpose of this paper is to accelerate cardiac diffusion tensor imaging (CDTI) by integrating low-rankness and compressed sensing. Methods: Diffusion-weighted images exhibit both transform sparsity and low-rankness. These properties can jointly be exploited to accelerate CDTI, especially when a phase map is applied to correct for the phase inconsistency across diffusion directions, thereby enhancing low-rankness. The proposed method is evaluated both ex vivo and in vivo, and is compared to methods using either a low-rank or sparsity constraint alone. Results: Compared to using a low-rank or sparsity constraint alone, the proposed method preserves more accurate helix angle features, the transmural continuum across the myocardium wall, and mean diffusivity at higher acceleration, while yielding significantly lower bias and higher intraclass correlation coefficient. Conclusion: Low-rankness and compressed sensing together facilitate acceleration for both ex vivo and in vivo CDTI, improving reconstruction accuracy compared to employing either constraint alone. Significance: Compared to previous methods for accelerating CDTI, the proposed method has the potential to reach higher acceleration while preserving myofiber architecture features, which may allow more spatial coverage, higher spatial resolution, and shorter temporal footprint in the future.

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Ma S, Nguyen CT, Christodoulou AG, Luthringer D, Kobashigawa J, Lee SE et al. Accelerated cardiac diffusion tensor imaging using joint low-rank and sparsity constraints. IEEE Transactions on Biomedical Engineering. 2018 Oct 1;65(10):2219-2230. 8239837. https://doi.org/10.1109/TBME.2017.2787111