Acceleration of high angular and spatial resolution diffusion imaging using compressed sensing with multichannel spiral data. Issue 1 (17th January 2014)
- Record Type:
- Journal Article
- Title:
- Acceleration of high angular and spatial resolution diffusion imaging using compressed sensing with multichannel spiral data. Issue 1 (17th January 2014)
- Main Title:
- Acceleration of high angular and spatial resolution diffusion imaging using compressed sensing with multichannel spiral data
- Authors:
- Mani, Merry
Jacob, Mathews
Guidon, Arnaud
Magnotta, Vincent
Zhong, Jianhui - Abstract:
- <abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="mrm25119-sec-0001" sec-type="section"> <title>Purpose</title> <p>To accelerate the acquisition of simultaneously high spatial and angular resolution diffusion imaging.</p> </sec> <sec id="mrm25119-sec-0002" sec-type="section"> <title>Methods</title> <p>Accelerated imaging is achieved by recovering the diffusion signal at all voxels simultaneously from under‐sampled k‐q space data using a compressed sensing algorithm. The diffusion signal at each voxel is modeled as a sparse complex Gaussian mixture model. The joint recovery scheme enables incoherent under‐sampling of the 5‐D k‐q space, obtained by randomly skipping interleaves of a multishot variable density spiral trajectory. This sampling and reconstruction strategy is observed to provide considerably improved reconstructions than classical k‐q under‐sampling and reconstruction schemes. The complex model enables to account for the noise statistics without compromising the computational efficiency and theoretical convergence guarantees. The reconstruction framework also incorporates compensation of motion induced phase errors that result from the multishot acquisition.</p> </sec> <sec id="mrm25119-sec-0003" sec-type="section"> <title>Results</title> <p>Reconstructions of the diffusion signal from under‐sampled data using the proposed method yields accurate results with errors less that 5% for different accelerations and<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="mrm25119-sec-0001" sec-type="section"> <title>Purpose</title> <p>To accelerate the acquisition of simultaneously high spatial and angular resolution diffusion imaging.</p> </sec> <sec id="mrm25119-sec-0002" sec-type="section"> <title>Methods</title> <p>Accelerated imaging is achieved by recovering the diffusion signal at all voxels simultaneously from under‐sampled k‐q space data using a compressed sensing algorithm. The diffusion signal at each voxel is modeled as a sparse complex Gaussian mixture model. The joint recovery scheme enables incoherent under‐sampling of the 5‐D k‐q space, obtained by randomly skipping interleaves of a multishot variable density spiral trajectory. This sampling and reconstruction strategy is observed to provide considerably improved reconstructions than classical k‐q under‐sampling and reconstruction schemes. The complex model enables to account for the noise statistics without compromising the computational efficiency and theoretical convergence guarantees. The reconstruction framework also incorporates compensation of motion induced phase errors that result from the multishot acquisition.</p> </sec> <sec id="mrm25119-sec-0003" sec-type="section"> <title>Results</title> <p>Reconstructions of the diffusion signal from under‐sampled data using the proposed method yields accurate results with errors less that 5% for different accelerations and <italic>b</italic>‐values. The proposed method is also shown to perform better than standard k‐q acceleration schemes.</p> </sec> <sec id="mrm25119-sec-0004" sec-type="section"> <title>Conclusions</title> <p>The proposed scheme can significantly accelerate the acquisition of high spatial and angular resolution diffusion imaging by accurately reconstructing crossing fiber architectures from under‐sampled data. Magn Reson Med 73:126–138, 2015. © 2014 Wiley Periodicals, Inc.</p> </sec> </abstract> … (more)
- Is Part Of:
- Magnetic resonance in medicine. Volume 73:Issue 1(2015:Jan.)
- Journal:
- Magnetic resonance in medicine
- Issue:
- Volume 73:Issue 1(2015:Jan.)
- Issue Display:
- Volume 73, Issue 1 (2015)
- Year:
- 2015
- Volume:
- 73
- Issue:
- 1
- Issue Sort Value:
- 2015-0073-0001-0000
- Page Start:
- 126
- Page End:
- 138
- Publication Date:
- 2014-01-17
- Subjects:
- Nuclear magnetic resonance -- Periodicals
Electron paramagnetic resonance -- Periodicals
616.07548 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1522-2594 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/mrm.25119 ↗
- Languages:
- English
- ISSNs:
- 0740-3194
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5337.798000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 4378.xml