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Bias field correction using grey-weighted distance transform applied on MR volumes

We present a method that produces data-dependent high-pass filters that can be used in, e.g., image restoration. MR volumes often suffer from bias field artifacts produced due to unsteady magnetic field and spatial variations in reception of the RF magnetic eld emitted by the subject. To cope with these artifacts, we propose a method based on the grey-weighted distance transform (GWDT). It first computes the spectrum of the MR volume using Fast Fourier Transform, and then computes the GWDT of the magnitude spectrum. The power spectrum computed using GWDT helps in designing a high-pass filter which is later used to correct the bias artifacts. Experimental results on close to 100 datasets demonstrate the effectiveness of our method.