Reduction of bias for sparsity promoting regularization in MPI
International Journal on Magnetic Particle Imaging 7 (2): 2112002 (2021)
Infinite Science Publishing
Magnetic Particle Imaging (MPI) is a tracer based medical imaging modality with great potential due to its high sensi-tivity, high spatial and temporal resolution, and its ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem, which can be addressed by regularization methods that lead to a reconstruction bias, which is apparent in a systematic mismatch between true and reconstructed tracer distribution. This is expressed in a background signal, a mismatch of the spatial support of the tracer distribution and a mismatch of its values. In this work, MPI reconstruction bias and its impact are investigated and a recently proposed debiasing method with significant bias reduction capabilities is adopted.