Tsanda, ArtyomArtyomTsandaKhalid, SadiaSadiaKhalidKnopp, TobiasTobiasKnoppMöddel, MartinMartinMöddel2025-04-042025-04-042025International Journal on Magnetic Particle Imaging 11 (1, Suppl 1): 2503058 (2025)https://hdl.handle.net/11420/55167Magnetic particle imaging (MPI) reconstructs the spatial distribution of magnetic nanoparticles on a fixed grid, the resolution of which is limited by the noise present in the system. This paper addresses the reconstruction problem while integrating single-image super-resolution for concentration maps. We introduce Neural Implicit Representations (NIR) as an image prior, enabling arbitrary grid size sampling after training. Experimental results using a spiral phantom measurement reveal that NIR-based reconstruction maintains image sharpness across diverse grid sizes, surpassing the two-stage Kaczmarz-ℓ2 reconstruction followed by bicubic up-sampling in preserving fine structural details. This technique has a potential for high-resolution MPI imaging without relying on extensive datasets.en2365-903320251, Suppl 1Infinite Science Publishinghttps://creativecommons.org/licenses/by/4.0/Technology::616: DeseasesComputer Science, Information and General Works::006: Special computer methodsNatural Sciences and Mathematics::530: PhysicsJournal Articlehttps://doi.org/10.15480/882.1500510.18416/IJMPI.2025.250305810.15480/882.15005Journal Article