Under-sampled functional MRI using low-rank plus sparse matrix decomposition

@article{Singh2015UndersampledFM,
  title={Under-sampled functional MRI using low-rank plus sparse matrix decomposition},
  author={Vimal Singh and Ahmed H. Tewfik and David B. Ress},
  journal={2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2015},
  pages={897-901}
}
High spatial resolution in functional magnetic resonance imaging improves its sensitivity to brain activation signals by reducing partial volume effects. However, the long acquisition times required for high spatial resolution limit the temporal resolution in fMRI studies. Consequently, the low temporal sampling bandwidth leads to increase in physiological noise and poor modeling of the functional activation dynamics. Thus, fast techniques capable of recovering fMRI time-series from under… CONTINUE READING