04.11.2022

Paper published in Transactions on Instrumentation and Measurement

Our paper "On the Receive Path Calibration of Magnetic Particle Imaging Systems" has been published in IEEE Transactions on Instrumentation and Measurement.

Magnetic nanoparticles are a valuable tool in many biomedical applications and can be used for diagnostic and therapeutic purposes. In magnetic particle imaging (MPI) and magnetic particle spectroscopy (MPS), the particles are subjected to a dynamic magnetic field and the particle magnetization response is simultaneously measured using one or multiple receive coils. Separating the particle signal from the feed-through signal is commonly done by advanced passive filtering, which distorts the particle signal. To correct this distortion, the transfer function of the receive chain needs to be known. While in principle, the transfer function can be simulated, due to imperfections in the electronic components, it is often more accurate to determine the transfer function in a calibration procedure. Although this system calibration, utilizing a calibration-coil setup, has been done by several research groups in the past, a general description of the underlying calibration model and methodology is still missing. In this article, we provide a general multi-channel calibration procedure for inductive receive paths in MPI and a blueprint to investigate model and method uncertainties. We generalized the calibration procedure to also cover nonorthogonal and nonhomogeneous receive coils. Finally, we showcase the calibration procedure and uncertainty analysis on our custom MPS system and use the MPI transfer functions of misaligned receive coils to decouple their superimposed receive signals from the receive path. The findings enable the comparison of MPI signals from different devices and can be used to normalize measurements and system functions in devices with exchangeable receive coils.

The entire methodology is described in the paper "On the Receive Path Calibration of Magnetic Particle Imaging Systems" by Florian Thieben, Tobias Knopp, Marija Boberg, Fynn Foerger, Matthias Graeser, and Martin Möddel, which you can find here.