MR image reconstruction from partial k-space using singularity function representation

Image reconstruction from partial k-space is an important matter in magnetic resonance imaging (MRI). The previously proposed methods are unable to cope with truncation artifacts without degrading image quality. We present a method that is particularly suitable for reconstructing magnetic resonance (MR) images from partial k-space by reducing substantially truncation artifacts while maintaining the spatial resolution of the image. The proposed method is based on the use of a so-called singularity function representation determined by singular points and singularity degrees. With this model, our strategy consists in restricting the singularity degrees within some dynamic range, beyond which the corresponding singular points are set to zero. The proposed method was evaluated on both simulated and human brain MR data. The results showed that this new strategy has significantly improved the reconstruction quality of partial k-space data