Noise suppression is essential for improving the reliability of functional MRI (fMRI), particularly at ultra–high field strengths where system- and receiver-related fluctuations become prominent. We introduce a hardware-informed denoising method, Coil Sensitivity Filter (CsFilter), which exploits spatial sensitivity relationships among receiver coil elements to identify and suppress non–brain-origin signal components. CsFilter operates in the frequency domain by retaining temporal fluctuations whose coil-amplitude ordering is consistent with receiver sensitivity profiles. Using 7T task-based fMRI data acquired with a 32-channel head coil, CsFilter produced robust increases in voxel-wise temporal signal-to-noise ratio relative to conventional high-pass filtering, with more than 62% of voxels showing greater than twofold improvement. Task-based analyses showed increased statistical strength, with mean t-values rising from 4.68 to 5.74 and median t-values from 4.39 to 5.28. These results indicate that coil-sensitivity–guided filtering provides an effective and complementary strategy for suppressing additive non–brain-origin fluctuations in multi-channel fMRI data.
Sung et al. (Thu,) studied this question.