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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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