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Abstract:
The subtle signal changes in functional magnetic resonance imaging (fMRI) can be easily overwhelmed by noise of various origins.
Spikes in the collected fMRI raw data often arise from high-duty usage of the scanner hardware and can introduce significant noise in the
image and thereby in the image time series. Consequently, the spikes will corrupt the functional data and degrade the result of functional
mapping. In this work, a simple method based on processing the time course of the k-space data are introduced and implemented to remove
the spikes in the acquired data. Application of the method to experimental data shows that the methods are robust and effective for
eliminating of spike-related noise in fMRI time series.
