Reduction of Artifacts in Images from MR Truncated Data Using Singularity Spectrum Analysis

In this paper, the theory of signal singularity spectrum analysis(SSA) is proposed. Using SSA theory, a new method is presented to reduce truncation artifacts in magnetic resonance (MR) image due to truncated spectrum data.In the scheme, after detecting signal singularity locations using wavelet analysis inspectrum domain, SSA mathematic model is constructed, where weight coefficientsare determined by known truncated spectrum data. Then, the remainder of thetruncated spectrum can be obtained using SSA. Experiment and simulation resultsshow that the SSA method will produce fewer artifacts in MR image from truncatedspectrum than existing methods.