Abstract #3068
Catching Physiological Noise: Comparison of DRIFTER in Image and k -Space
Arno Solin 1 , Simo Srkk 1 , Aapo Nummenmaa 2 , Aki Vehtari 1 , Toni Auranen 3 , and Fa-Hsuan Lin 1,4
1
Department of Biomedical Engineering and
Computational Science, Aalto University, Espoo, Finland,
2
Athinoula
A. Martinos Center for Biomedical Imaging, Massachusetts
General Hospital, Boston, MA, United States,
3
Advanced
Magnetic Imaging Centre, Aalto NeuroImaging, Aalto
University, Espoo, Finland,
4
Institute
of Biomedical Engineering, National Taiwan University,
Taipei, Taiwan
We present how the DRIFTER method for removal and
modeling of physiological noise can be extended to
complex-valued images and raw
k
-space
data. We compare the amplitude maps of the reconstructed
cardiac noise component in fast fMRI data. The
experiments suggest that catching the noise at an early
stage of data processing can give better estimates of
the noise influence in the data. Consequently, also the
actual data component can be improved by removing the
physiological noise before image reconstruction, which
eliminates aliasing of the structural noise in the image
data.
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