Deep image prior for alternating direction method of multipliers reconstruction of experimental magnetic particle imaging data

This work presents an on-the-fly training Deep Image Prior (DIP) integrated into an Alternating Direction Method of Multipliers (ADMM) algorithm for Magnetic Particle Imaging (MPI) system-matrix reconstruction. Experimental data results indicate competitive quality and robustness, supporting the approach as a practical alternative to classical Tikhonov.