Baseline drift and physiological noise removal in high field FMRI data using kernel PCA

@article{Song2008BaselineDA,
  title={Baseline drift and physiological noise removal in high field FMRI data using kernel PCA},
  author={Xiaomu Song and T. Ji and A. Wyrwicz},
  journal={2008 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2008},
  pages={441-444}
}
  • Xiaomu Song, T. Ji, A. Wyrwicz
  • Published 2008
  • Computer Science
  • 2008 IEEE International Conference on Acoustics, Speech and Signal Processing
Baseline drift and physiological (cardiac and respiratory) fluctuations are among major sources contaminating blood oxygenation level dependent (BOLD) signals in high field functional magnetic resonance imaging (fMRI). Automatically detecting and removing them have been long-standing problems. We propose here a new method, utilizing kernel principal component analysis (KPCA) and frequency analysis, to detect and remove the noise from fMRI data. Differing from thermal noise, the main energy of… Expand
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