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  Comparison of sampling strategies and sparsifying transforms to improve compressed sensing diffusion spectrum imaging

Paquette, M., Merlet, S., Gilbert, G., Deriche, R., & Descoteaux, M. (2015). Comparison of sampling strategies and sparsifying transforms to improve compressed sensing diffusion spectrum imaging. Magnetic Resonance in Medicine, 73(1), 401-416. doi:10.1002/mrm.25093.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-B8CF-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-B8D0-F
Genre: Journal Article

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 Creators:
Paquette, Michael1, Author              
Merlet, Sylvain1, Author
Gilbert, Guillaume1, Author
Deriche, Rachid1, Author
Descoteaux, Maxime1, Author
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1External Organizations, ou_persistent22              

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Free keywords: Compressive sensing; Diffusion spectrum imaging; Diffusion‐weighted imaging; Ensemble average propagator; Orientation distribution function; Kurtosis
 Abstract: Purpose Diffusion Spectrum Imaging enables to reconstruct the ensemble average propagator (EAP) at the expense of having to acquire a large number of measurements. Compressive sensing offers an efficient way to decrease the required number of measurements. The purpose of this work is to perform a thorough experimental comparison of three sampling strategies and six sparsifying transforms to show their impact when applied to accelerate compressive sensing‐diffusion spectrum imaging. Methods We propose a novel sampling scheme that assures uniform angular and random radial q‐space samples. We also compare and implement six discrete sparse representations of the EAP and thoroughly evaluate them on synthetic and real data using metrics from the full EAP, kurtosis, and orientation distribution function. Results The discrete wavelet transform with Cohen–Daubechies–Feauveau 9/7 wavelets and uniform angular sampling in combination with random radial sampling showed to be better than other tested techniques to accurately reconstruct the EAP and its features. Conclusion It is important to jointly optimize the sampling scheme and the sparsifying transform to obtain accelerated compressive sensing‐diffusion spectrum imaging. Experiments on synthetic and real human brain data show that one can robustly recover both radial and angular EAP features while undersampling the acquisition to 64 measurements (undersampling factor of 4).

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Language(s): eng - English
 Dates: 2013-11-212013-02-162013-12-022014-01-292015-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Degree: -

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Title: Magnetic Resonance in Medicine
Source Genre: Journal
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Publ. Info: New York : Wiley-Liss
Pages: - Volume / Issue: 73 (1) Sequence Number: - Start / End Page: 401 - 416 Identifier: ISSN: 0740-3194
CoNE: https://pure.mpg.de/cone/journals/resource/954925538149