INTRODUCTION
The MPIRF is developed by Python 3.8. It could integrate different MPI reconstruction algorithm and realize the reconstruction function from the voltage signal of the magnetic nanoparticle to the image signal.
The current version provides two main function files: MPIRFmain.py and MPIRFUImain.py.
In Windows system, it also include a version with GPU. The test of the version were performed using the following hardware:
GPU NVIDIA GeForce GTX 1070 8G
This project has been displayed by the Open-soure Magnetic Particle Imaging community: https://os-mpi.github.io/RecoFramework/
ARCHITECTURE
Specifically see the paper:
INSTALLATION
The following dependent libraries need to be installed:
pip install numpy
pip install scipy
pip install h5py
pip install matplotlib
pip install numba
pip install scikit-image
pip install opencv-python
To run MPIRFUImain.py, you also need to install:
pip install pyqt5
RUNING THE EXAMPLE
The simulation process data is written to the h5 file under the phantom path.
python MPIRFmain.py, batch Simulation for 2D MPI, the set of simulation parameters is shown in the figure:
python MPIRFUImain.py, the result of the runing is shown in the figure:
Test Parameters：
Particle Parameters：
| Particle Temperature | 20 |
| Particle Diameter | 25 |
| Particle Saturation Magnetization | 0.6 |
| Particle Concentration | 50 |
MPI Scanner Parameters (Lissajous)：
| Selection Field Gradient(x,y) | 2, 2 |
| Drive Field Frequency(x,y) | 24.51, 26.042 |
| Drive Field Amplitude(x,y) | 12, 12 |
| Repeat Time | 652.8 |
| Sample Frequency | 2.5 |
Repeat Time:
MPI Scanner Parameters (Cartesian)：
| Selection Field Gradient(x,y) | 2, 2 |
| Drive Field Frequency(x,y) | 25,1 |
| Drive Field Amplitude(x,y) | 12, 12 |
| Repeat Time | 1000 |
| Sample Frequency | 2.5 |
Repeat Time:
Notice
Use this platform to publish papers, please cite
Shen, Y, Hu, C, Zhang, P, Tian, J, Hui, H. A novel software framework for magnetic particle imaging reconstruction. Int J Imaging Syst Technol. 2022; 1- 14. doi:10.1002/ima.22707