Separation of veins from activated brain tissue in functional magnetic resonance images at 1.5T

A feasibility study was conducted to segment 1.5T functional magnetic resonance images (fMRIs) into gray matter and veins using individual pixel intensity difference and temporal phase delay as two correlated parameters in 1.5T gradient echo images. The time-course of each pixel in gradient echo images acquired during visual stimulation with a checkerboard flashing at 8 Hz was correlated to the stimulation on-off sequence to identify activated pixels, and the temporal delay of each activated pixel was computed by fitting its time-course to a reference sinusoidal function. A histogram of the product of each pixel´s intensity (in the activated image) and corresponding temporal delay could be fitted to a bimodal distribution, which was then used to segment the functional image into veins and activated brain tissue. The results show relatively good demarcation between large veins and activated gray matter using this method