Name
Abstract | ||
|---|---|---|
Diffusion-weighted MRI measures the direction and scale of the local diffusion process in every voxel through its spectrum in q-space, typically acquired in one or more shells. Recent developments in microstructure imaging and multi-tissue decomposition have sparked renewed attention in the radial b-value dependence of the signal. Applications in motion correction and outlier rejection, therefore, require a compact linear signal representation that extends over the radial as well as angular domain. Here, we introduce SHARD, a data-driven representation of the q-space signal based on spherical harmonics and a radial decomposition into orthonormal components. This representation provides a complete, orthogonal signal basis, tailored to the spherical geometry of q-space, and calibrated to the data at hand. We demonstrate that the rank-reduced decomposition outperforms model-based alternatives in human brain data, while faithfully capturing the micro- and meso-structural information in the signal. Furthermore, we validate the potential of joint radial-spherical as compared with single-shell representations. As such, SHARD is optimally suited for applications that require low-rank signal predictions, such as motion correction and outlier rejection. Finally, we illustrate its application for the latter using outlier robust regression. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TMI.2018.2873736 | IEEE TRANSACTIONS ON MEDICAL IMAGING |
Keywords | Field | DocType |
Diffusion-weighted imaging, multi-shell HARDI, blind source separation, dimensionality reduction | Voxel,Computer vision,Dimensionality reduction,Spherical harmonics,Outlier,Algorithm,Spherical geometry,Shard,Orthonormal basis,Artificial intelligence,Blind signal separation,Mathematics | Journal |
Volume | Issue | ISSN |
38 | 3 | 0278-0062 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daan Christiaens | 1 | 212 | 9.23 |
| Lucilio Cordero-Grande | 2 | 140 | 16.15 |
| Jana Hutter | 3 | 7 | 3.47 |
| Anthony N Price | 4 | 253 | 15.32 |
| Maria Deprez | 5 | 1 | 2.38 |
| Jo Hajnal | 6 | 1796 | 119.03 |
| Jacques-Donald Tournier | 7 | 1014 | 61.91 |