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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Journal of Imaging |
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| Online Access: | https://www.mdpi.com/2313-433X/7/11/226 |
| _version_ | 1797509861529878528 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:23:43Z |
| format | Article |
| id | doaj.art-76689daedde14e7fb688f713995abadf |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-03-10T05:23:43Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-76689daedde14e7fb688f713995abadf2023-11-22T23:52:14ZengMDPI AGJournal of Imaging2313-433X2021-10-0171122610.3390/jimaging7110226Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical PriorsMarica Pesce0Audrey Repetti1Anna Auría2Alessandro Daducci3Jean-Philippe Thiran4Yves Wiaux5Institute of Sensors Signals and Systems (ISSS), Heriot-Watt University, Edinburgh EH14 4AS, UKInstitute of Sensors Signals and Systems (ISSS), Heriot-Watt University, Edinburgh EH14 4AS, UKSignal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, SwitzerlandDepartment of Computer Science, University of Verona, 37134 Verona, ItalySignal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, SwitzerlandInstitute of Sensors Signals and Systems (ISSS), Heriot-Watt University, Edinburgh EH14 4AS, UKHigh 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.https://www.mdpi.com/2313-433X/7/11/226diffusion MRIHARDIcompressed sensingoptimizationdata acquisitionreconstruction |
| spellingShingle | 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 Journal of Imaging diffusion MRI HARDI compressed sensing optimization data acquisition reconstruction |
| title | 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_short | 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 |
| topic | diffusion MRI HARDI compressed sensing optimization data acquisition reconstruction |
| url | https://www.mdpi.com/2313-433X/7/11/226 |
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