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High-resolution $dynamic^{31}$P-MRSI using a low-rank tensor model
| Content Provider | Scilit |
|---|---|
| Author | YuChi, Liu Ma, Chao Clifford, Bryan Gu, Yuning Lam, Fan Yu, Xin Liang, Zhi-Pei |
| Copyright Year | 2017 |
| Description | Journal: Magnetic Resonance in Medicine To develop a rapid 31 P-MRSI method with high spatiospectral resolution using low-rank tensor-based data acquisition and image reconstruction. The multidimensional image function of 31 P-MRSI is represented by a low-rank tensor to capture the spatial-spectral-temporal correlations of data. A hybrid data acquisition scheme is used for sparse sampling, which consists of a set of "training" data with limited k-space coverage to capture the subspace structure of the image function, and a set of sparsely sampled "imaging" data for high-resolution image reconstruction. An explicit subspace pursuit approach is used for image reconstruction, which estimates the bases of the subspace from the "training" data and then reconstructs a high-resolution image function from the "imaging" data. We have validated the feasibility of the proposed method using phantom and in vivo studies on a 3T whole-body scanner and a 9.4T preclinical scanner. The proposed method produced high-resolution static 31 P-MRSI images (i.e., 6.9 × 6.9 × 10 mm3 nominal resolution in a 15-min acquisition at 3T) and high-resolution, high-frame-rate dynamic 31 P-MRSI images (i.e., 1.5 × 1.5 × 1.6 mm3 nominal resolution, 30 s/frame at 9.4T). Dynamic spatiospectral variations of 31 P-MRSI signals can be efficiently represented by a low-rank tensor. Exploiting this mathematical structure for data acquisition and image reconstruction can lead to fast 31 P-MRSI with high resolution, frame-rate, and SNR. Magn Reson Med 78:419-428, 2017. © 2017 International Society for Magnetic Resonance in Medicine. |
| Related Links | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562044/pdf |
| Ending Page | 428 |
| Page Count | 10 |
| Starting Page | 419 |
| e-ISSN | 15222594 |
| DOI | 10.1002/mrm.26762 |
| Journal | Magnetic Resonance in Medicine |
| Issue Number | 2 |
| Volume Number | 78 |
| Language | English |
| Publisher | Wiley-Blackwell |
| Publisher Date | 2017-05-28 |
| Access Restriction | Open |
| Subject Keyword | Journal: Magnetic Resonance in Medicine Radiology, Nuclear Medicine and Imaging Partial Separability Subspace Modeling |
| Content Type | Text |
| Resource Type | Article |
