Detection of Brainwaves in Magnetic Resonance Images Using Fast Fourier Transform (FFT)

The purpose of this study is to detect brainwave and physiological signals from MR images by applying Fourier transform and Shannon's sampling theorem. Ten datasets were obtained from 10 subjects using the gradient echo - echo planar imaging (GE-EPI) sequence with a 3.0 T Phillips scanner. 1500 images on an axial plane consisting of the eyeballs were acquired for each subject. MATLAB was used for the image processing. The 1500 time frame signals were being Fourier transformed to produce the frequency spectral. Then, a bandpass filter was applied to filter out the unwanted signals in order to detect the brainwaves and physiological signals. Our study showed that the axonal magnetic field was 6.64±0.27 pT for delta waves, 6.58±2.28 pT for theta waves, 8.33±1.53 nT for the respiration signal, and 9.01±4.16 nT for the heartbeat signal. The brainwaves were found in the occipital and temporal lobes. The heartbeat was concentrated around the circle of Willis while the respiration signal around the subarachnoid space and superior sagittal sinus.