Name
Abstract | ||
|---|---|---|
Magnetic Particle Imaging (MPI) is a promising new tracer-based imaging modality. The steady-state, nonlinear magnetization physics most fundamental to MPI typically predicts improving resolution with increasing tracer magnetic core size. For larger tracers, and given typical excitation slew rates, this steady-state prediction is compromised by dynamic processes that induce a significant secondary blur and prevent us from achieving high resolution using larger tracers. Here we propose a new method of excitation and signal encoding in MPI we call pulsed MPI to overcome this phenomenon. Pulsed MPI allows us to directly encode the steady-state magnetic physics into the time-domain signal. This in turn gives rise to a simple reconstruction algorithm to obtain images free of secondary relaxation-induced blur. Here we provide a detailed description of our approach in 1D, discuss how it compares with alternative approaches, and show experimental data demonstrating better than 500 μm resolution (at 7 T/m) with large tracers. Finally we show experimental images from a 2D implementation. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TMI.2019.2898202 | IEEE transactions on medical imaging |
Keywords | Field | DocType |
Magnetic resonance imaging,Steady-state,Magnetic cores,Image resolution,Magnetic domains,Signal resolution | Magnetic particle imaging,Computer vision,Computational physics,Nonlinear system,Magnetization,Excitation,Reconstruction algorithm,Magnetic core,Artificial intelligence,Image resolution,Magnetic domain,Mathematics | Journal |
Volume | Issue | ISSN |
38 | 10 | 1558-254X |
Citations | PageRank | References |
2 | 0.47 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhi Wei Tay | 1 | 2 | 0.81 |
| Daniel Hensley | 2 | 2 | 1.14 |
| Jie Ma | 3 | 2 | 0.47 |
| Prashant Chandrasekharan | 4 | 2 | 0.81 |
| bo zheng | 5 | 25 | 7.29 |
| Patrick W. Goodwill | 6 | 75 | 10.14 |
| Steven Conolly | 7 | 2 | 0.47 |