Application of compressed sensing to in vivo 3D 19F CSI

The application of CS to 3D 19F CSI enables in vivo applications in significantly reduced measurement times while preserving the relevant spectroscopic and biological information. [Display omitted] . ► Application of CS to 3D 19F CSI. ► CS algorithm without regularization parameters and strict data...

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Bibliographic Details
Published in:Journal of magnetic resonance (1997) 2010-12, Vol.207 (2), p.262-273
Main Authors: Kampf, T., Fischer, A., Basse-Lüsebrink, T.C., Ladewig, G., Breuer, F., Stoll, G., Jakob, P.M., Bauer, W.R.
Format: Article
Language:English
Subjects:
19F
Algorithms
Animals
Compressed sensing
Computer Simulation
CSI
Data Interpretation, Statistical
Fluorine - chemistry
Image Processing, Computer-Assisted
Ischemic Attack, Transient - pathology
Magnetic Resonance Imaging - methods
Mice
Mice, Inbred C57BL
Phantoms, Imaging
Reference Values
Reproducibility of Results
Sparse
Thrombosis - pathology
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Summary:The application of CS to 3D 19F CSI enables in vivo applications in significantly reduced measurement times while preserving the relevant spectroscopic and biological information. [Display omitted] . ► Application of CS to 3D 19F CSI. ► CS algorithm without regularization parameters and strict data consistency. ► Detailed investigation on the effect of different noise levels and acceleration factors. ► Reduced in vivo measurement time. This study shows how applying compressed sensing (CS) to 19F chemical shift imaging (CSI) makes highly accurate and reproducible reconstructions from undersampled datasets possible. The missing background signal in 19F CSI provides the required sparsity needed for application of CS. Simulations were performed to test the influence of different CS-related parameters on reconstruction quality. To test the proposed method on a realistic signal distribution, the simulation results were validated by ex vivo experiments. Additionally, undersampled in vivo 3D CSI mouse datasets were successfully reconstructed using CS. The study results suggest that CS can be used to accurately and reproducibly reconstruct undersampled 19F spectroscopic datasets. Thus, the scanning time of in vivo 19F CSI experiments can be significantly reduced while preserving the ability to distinguish between different 19F markers. The gain in scan time provides high flexibility in adjusting measurement parameters. These features make this technique a useful tool for multiple biological and medical applications.
ISSN:1090-7807
1096-0856
DOI:10.1016/j.jmr.2010.09.006