Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors

High spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisition times. We propose a method to recover intra-voxel fiber configurations at high spatio-angular resolution relying on...

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Autores principales:	Marica Pesce, Audrey Repetti, Anna Auría, Alessandro Daducci, Jean-Philippe Thiran, Yves Wiaux
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	diffusion MRI HARDI compressed sensing optimization data acquisition reconstruction Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/76689daedde14e7fb688f713995abadf
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spelling	oai:doaj.org-article:76689daedde14e7fb688f713995abadf2021-11-25T18:03:25ZFast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors10.3390/jimaging71102262313-433Xhttps://doaj.org/article/76689daedde14e7fb688f713995abadf2021-10-01T00:00:00Zhttps://www.mdpi.com/2313-433X/7/11/226https://doaj.org/toc/2313-433XHigh spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisition times. We propose a method to recover intra-voxel fiber configurations at high spatio-angular resolution relying on a 3D kq-space under-sampling scheme to enable accelerated acquisitions. The inverse problem for the reconstruction of the fiber orientation distribution (FOD) is regularized by a <i>structured sparsity</i> prior promoting simultaneously voxel-wise sparsity and spatial smoothness of fiber orientation. Prior knowledge of the spatial distribution of white matter, gray matter, and cerebrospinal fluid is also leveraged. A minimization problem is formulated and solved via a stochastic forward–backward algorithm. Simulations and real data analysis suggest that accurate FOD mapping can be achieved from severe kq-space under-sampling regimes potentially enabling high spatio-angular resolution dMRI in the clinical setting.Marica PesceAudrey RepettiAnna AuríaAlessandro DaducciJean-Philippe ThiranYves WiauxMDPI AGarticlediffusion MRIHARDIcompressed sensingoptimizationdata acquisitionreconstructionPhotographyTR1-1050Computer applications to medicine. Medical informaticsR858-859.7Electronic computers. Computer scienceQA75.5-76.95ENJournal of Imaging, Vol 7, Iss 226, p 226 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	diffusion MRI HARDI compressed sensing optimization data acquisition reconstruction Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95
spellingShingle	diffusion MRI HARDI compressed sensing optimization data acquisition reconstruction Photography TR1-1050 Computer applications to medicine. Medical informatics R858-859.7 Electronic computers. Computer science QA75.5-76.95 Marica Pesce Audrey Repetti Anna Auría Alessandro Daducci Jean-Philippe Thiran Yves Wiaux Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors
description	High spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisition times. We propose a method to recover intra-voxel fiber configurations at high spatio-angular resolution relying on a 3D kq-space under-sampling scheme to enable accelerated acquisitions. The inverse problem for the reconstruction of the fiber orientation distribution (FOD) is regularized by a <i>structured sparsity</i> prior promoting simultaneously voxel-wise sparsity and spatial smoothness of fiber orientation. Prior knowledge of the spatial distribution of white matter, gray matter, and cerebrospinal fluid is also leveraged. A minimization problem is formulated and solved via a stochastic forward–backward algorithm. Simulations and real data analysis suggest that accurate FOD mapping can be achieved from severe kq-space under-sampling regimes potentially enabling high spatio-angular resolution dMRI in the clinical setting.
format	article
author	Marica Pesce Audrey Repetti Anna Auría Alessandro Daducci Jean-Philippe Thiran Yves Wiaux
author_facet	Marica Pesce Audrey Repetti Anna Auría Alessandro Daducci Jean-Philippe Thiran Yves Wiaux
author_sort	Marica Pesce
title	Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors
title_short	Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors
title_full	Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors
title_fullStr	Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors
title_full_unstemmed	Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors
title_sort	fast fiber orientation estimation in diffusion mri from kq-space sampling and anatomical priors
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/76689daedde14e7fb688f713995abadf
work_keys_str_mv	AT maricapesce fastfiberorientationestimationindiffusionmrifromkqspacesamplingandanatomicalpriors AT audreyrepetti fastfiberorientationestimationindiffusionmrifromkqspacesamplingandanatomicalpriors AT annaauria fastfiberorientationestimationindiffusionmrifromkqspacesamplingandanatomicalpriors AT alessandrodaducci fastfiberorientationestimationindiffusionmrifromkqspacesamplingandanatomicalpriors AT jeanphilippethiran fastfiberorientationestimationindiffusionmrifromkqspacesamplingandanatomicalpriors AT yveswiaux fastfiberorientationestimationindiffusionmrifromkqspacesamplingandanatomicalpriors
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Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors

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