Magnetic Particle Imaging (MPI) is a novel technique for remotely detecting magnetic nanoparticle (MNP) tracers, with several applications in biomedical imaging and diagnosis, as well as materials research. MPI relies on the non-linear magnetization response of MNPs when exposed to time-varying magnetic fields. Special arrangements of magnets or electromagnets allow selectively saturating the particles' magnetization over time in such a way that the distribution of MNPs can be measured as a function of space, through the generation of a moving field-free point (FFP) which saturates all particles but the ones near the no-field region.

However, the time signal of the varying magnetic response alone is not enough to deduce the spatial distribution of the MNPs. Obtaining this information requires two additional steps, in which we first relate the time signal to its corresponding spatial position to get an image, and then deblur this image based on the knowledge of the experimental setup and its point spread function (PSF). This process in mathematical terms is also known as solving an inverse problem and amounts to carefully balancing between a good fit to the observed data and a realistic reconstruction.

This web application intends to give the user a tool to see for themselves how different experimental setups can influence the quality and reliability of Magnetic Particle Imaging and can help to illustrate the challenges researchers at NIST face when trying to improve this novel measurement technology.