Abstract：
:In this paper, we exploit the ability of Compressed Sensing (CS) to recover the whole 3D Diffusion MRI (dMRI) signal from a limited number of samples while efficiently recovering important diffusion features such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF). Some attempts to use CS in estimating diffusion signals have been done recently. However, this was mainly an experimental insight of CS capabilities in dMRI and the CS theory has not been fully exploited. In this work, we also propose to study the impact of the sparsity, the incoherence and the RIP property on the reconstruction of diffusion signals. We show that an efficient use of the CS theory enables to drastically reduce the number of measurements commonly used in dMRI acquisitions. Only 20-30 measurements, optimally spread on several b-value shells, are shown to be necessary, which is less than previous attempts to recover the diffusion signal using CS. This opens an attractive perspective to measure the diffusion signals in white matter within a reduced acquisition time and shows that CS holds great promise and opens new and exciting perspectives in diffusion MRI (dMRI).
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Merlet SL,Deriche Rdoi
10.1016/j.media.2013.02.010subject
Has Abstractpub_date
2013-07-01 00:00:00pages
556-72issue
5eissn
1361-8415issn
1361-8423pii
S1361-8415(13)00025-Xjournal_volume
17pub_type
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journal_title：Medical image analysis
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pub_type： 杂志文章
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journal_title：Medical image analysis
pub_type： 社论
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更新日期：2016-10-01 00:00:00
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更新日期：2019-07-01 00:00:00
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journal_title：Medical image analysis
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journal_title：Medical image analysis
pub_type： 杂志文章
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更新日期：2008-08-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.07.002
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journal_title：Medical image analysis
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journal_title：Medical image analysis
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journal_title：Medical image analysis
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journal_title：Medical image analysis
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journal_title：Medical image analysis
pub_type： 杂志文章
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更新日期：2018-10-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
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更新日期：2019-12-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(02)00064-6
更新日期：2002-12-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.01.004
更新日期：2017-04-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.09.004
更新日期：2006-04-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
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更新日期：2015-10-01 00:00:00
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更新日期：2021-01-01 00:00:00
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journal_title：Medical image analysis
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journal_title：Medical image analysis
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更新日期：2014-02-01 00:00:00
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journal_title：Medical image analysis
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journal_title：Medical image analysis
pub_type： 杂志文章,评审
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更新日期：2006-04-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
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更新日期：2007-12-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
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更新日期：1996-03-01 00:00:00
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journal_title：Medical image analysis
pub_type： 杂志文章
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更新日期：2020-08-01 00:00:00
