Magnetic particle imaging (MPI) is a new tomographic imaging technique capable of determining the spatial distribution of superparamagnetic iron oxide particles at high temporal and spatial resolution. Reconstruction of the particle distribution requires the system function to be known. In almost all other tomographic imaging techniques, a basic mathematical model of the system function exists, so that for reconstruction of an image, only measured data from the object under examination have to be provided. Due to the complex behavior of the particle dynamics, this is more complicated in MPI. Therefore, to date, the system function is measured in a tedious calibration procedure. To this end, a small delta sample is moved to each position inside the measuring field, while the magnetization response is acquired consecutively. However, although this measurement-based approach provides a good estimate of the system function, it has several drawbacks. Most important, the measured system function contains noise, which limits the size of the delta sample and in turn the resolution of the sampling grid. In this work, the noise induced limitations of the measurement-based system function are investigated in a simulation study. More precisely, the influence of the system function noise and the size of the delta sample on the resulting image quality after reconstruction are analyzed.
|Title of host publication
|Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging
|Number of pages
|Published - 15.06.2010
|SPIE Medical Imaging 2010
- San Diego, United States
Duration: 13.02.2010 → 18.02.2010