LAUSR

The frequency component compression method (FCCM) has been widely used in magnetic particle imaging (MPI) technology to improve reconstruction efficiency. This method can reduce the reconstruction time by using the signal-to-noise ratio (SNR) feature to remove high noise frequency components. To further accelerate the reconstruction, a dual-feature frequency component compression method (DF-FCCM) was developed herein. A new energy spectral density (ESD) feature was introduced to describe the noise level of measurement signal. By using the SNR feature and the ESD feature, the DF-FCCM can select valuable frequency components that contain low noise both in the measurement signal and the system matrix. The reconstruction time can be reduced by using fewer frequency components that contain more valuable information. The efficiency and the robustness of the proposed method was validated through extensive simulation experiments. Further real experiments based on the OpenMPI data set verified that the DF-FCCM can be applied in real MPI reconstruction. Compared to the previous SNR-FCCM, the DF-FCCM can achieve similar or better reconstruction quality by using 25% reconstruction time. The proposed method can efficiently improve the reconstruction efficiency and potential to improve the online MPI imaging, which is essential for pre-clinical and clinical applications.