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Estimation of the CSA-ODF using Bayesian compressed sensing of multi-shell HARDI.

Publication ,  Journal Article
Duarte-Carvajalino, JM; Lenglet, C; Xu, J; Yacoub, E; Ugurbil, K; Moeller, S; Carin, L; Sapiro, G
Published in: Magnetic resonance in medicine
November 2014

Diffusion MRI provides important information about the brain white matter structures and has opened new avenues for neuroscience and translational research. However, acquisition time needed for advanced applications can still be a challenge in clinical settings. There is consequently a need to accelerate diffusion MRI acquisitions.A multi-task Bayesian compressive sensing (MT-BCS) framework is proposed to directly estimate the constant solid angle orientation distribution function (CSA-ODF) from under-sampled (i.e., accelerated image acquisition) multi-shell high angular resolution diffusion imaging (HARDI) datasets, and accurately recover HARDI data at higher resolution in q-space. The proposed MT-BCS approach exploits the spatial redundancy of the data by modeling the statistical relationships within groups (clusters) of diffusion signal. This framework also provides uncertainty estimates of the computed CSA-ODF and diffusion signal, directly computed from the compressive measurements. Experiments validating the proposed framework are performed using realistic multi-shell synthetic images and in vivo multi-shell high angular resolution HARDI datasets.Results indicate a practical reduction in the number of required diffusion volumes (q-space samples) by at least a factor of four to estimate the CSA-ODF from multi-shell data.This work presents, for the first time, a multi-task Bayesian compressive sensing approach to simultaneously estimate the full posterior of the CSA-ODF and diffusion-weighted volumes from multi-shell HARDI acquisitions. It demonstrates improvement of the quality of acquired datasets by means of CS de-noising, and accurate estimation of the CSA-ODF, as well as enables a reduction in the acquisition time by a factor of two to four, especially when "staggered" q-space sampling schemes are used. The proposed MT-BCS framework can naturally be combined with parallel MR imaging to further accelerate HARDI acquisitions.

Duke Scholars

Published In

Magnetic resonance in medicine

DOI

EISSN

1522-2594

ISSN

0740-3194

Publication Date

November 2014

Volume

72

Issue

5

Start / End Page

1471 / 1485

Related Subject Headings

  • White Matter
  • Nuclear Medicine & Medical Imaging
  • Image Processing, Computer-Assisted
  • Image Enhancement
  • Humans
  • Diffusion Magnetic Resonance Imaging
  • Data Compression
  • Bayes Theorem
  • 4003 Biomedical engineering
  • 0903 Biomedical Engineering
 

Citation

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Duarte-Carvajalino, J. M., Lenglet, C., Xu, J., Yacoub, E., Ugurbil, K., Moeller, S., … Sapiro, G. (2014). Estimation of the CSA-ODF using Bayesian compressed sensing of multi-shell HARDI. Magnetic Resonance in Medicine, 72(5), 1471–1485. https://doi.org/10.1002/mrm.25046
Duarte-Carvajalino, Julio M., Christophe Lenglet, Junqian Xu, Essa Yacoub, Kamil Ugurbil, Steen Moeller, Lawrence Carin, and Guillermo Sapiro. “Estimation of the CSA-ODF using Bayesian compressed sensing of multi-shell HARDI.Magnetic Resonance in Medicine 72, no. 5 (November 2014): 1471–85. https://doi.org/10.1002/mrm.25046.
Duarte-Carvajalino JM, Lenglet C, Xu J, Yacoub E, Ugurbil K, Moeller S, et al. Estimation of the CSA-ODF using Bayesian compressed sensing of multi-shell HARDI. Magnetic resonance in medicine. 2014 Nov;72(5):1471–85.
Duarte-Carvajalino, Julio M., et al. “Estimation of the CSA-ODF using Bayesian compressed sensing of multi-shell HARDI.Magnetic Resonance in Medicine, vol. 72, no. 5, Nov. 2014, pp. 1471–85. Epmc, doi:10.1002/mrm.25046.
Duarte-Carvajalino JM, Lenglet C, Xu J, Yacoub E, Ugurbil K, Moeller S, Carin L, Sapiro G. Estimation of the CSA-ODF using Bayesian compressed sensing of multi-shell HARDI. Magnetic resonance in medicine. 2014 Nov;72(5):1471–1485.
Journal cover image

Published In

Magnetic resonance in medicine

DOI

EISSN

1522-2594

ISSN

0740-3194

Publication Date

November 2014

Volume

72

Issue

5

Start / End Page

1471 / 1485

Related Subject Headings

  • White Matter
  • Nuclear Medicine & Medical Imaging
  • Image Processing, Computer-Assisted
  • Image Enhancement
  • Humans
  • Diffusion Magnetic Resonance Imaging
  • Data Compression
  • Bayes Theorem
  • 4003 Biomedical engineering
  • 0903 Biomedical Engineering