In magnetic particle imaging (MPI), the relation between the particle distribution and the measurement signal can be described by a linear system of equations. For 1D imaging, it can be shown that the system matrix can be expressed as a product of a convolution matrix and a Chebyshev transformation matrix. For multidimensional imaging, the structure of the MPI system matrix is not yet fully explored as the sampling trajectory complicates the physical model. It has been experimentally found that the MPI system matrix rows have symmetries and look similar to the tensor products of Chebyshev polynomials. In this work we will mathematically prove that the 2D MPI system matrix has symmetries that can be used for matrix compression.
