A semi-automatic method for SWI processing

Susceptibility weighted imaging (SWI) is a new magnetic resonance imaging (MRI) technique that uses the susceptibility differences (e. g. between venous blood and the surrounding tissue) to provide the tissue contrast. To obtain the susceptibility-related contrast, magnitude and phase MR images are subjected to a series of processing steps. The phase image is firstly high-pass filtered to remove the background field effects. Then, a phase mask is created and multiplied a define number of times by the magnitude image to generate the SWI image. These processing steps are regulated by two main parameters: the window size of the filter and the multiplication factor of the phase mask. Currently, both these parameters are properly chosen by visually inspecting the appearance of the SWI image. In this paper a new semiautomatic method for determining the optimal parameters for SWI processing is presented. This method is based on the maximization of the contrast-to-noise ratio (CNR) between venous blood and its surroundings. The influence of the processing parameters on the CNR of the final SWI image is discussed. Results on real data demonstrate the effectiveness of the proposed method in enhancing the visualization of the venous vasculature in the brain.