[www] [BibTex]

Note: inproceedings, model-based

Abstract: To date a system matrix has to be obtained through a tedious calibration measurement when employing a systemmatrix-based reconstruction in magnetic particle imaging. This problem can be effectively addressed by model-based reconstruction, which takes into account both particle and scanner parameters. In this study, we focus onthe scanner parameters and in particular on the fact that the fields of experimental systems are imperfect. Forexperimental Lissajous-type data we show that the modeling error can be substantially reduced by about 18 % by incorporating field imperfections in both the transmit and receive coils.

[www]

Note: inproceedings, model-based

Abstract: To date a system matrix has to be obtained through a tedious calibration measurement when employing a systemmatrix-based reconstruction in magnetic particle imaging. This problem can be effectively addressed by model-based reconstruction, which takes into account both particle and scanner parameters. In this study, we focus onthe scanner parameters and in particular on the fact that the fields of experimental systems are imperfect. Forexperimental Lissajous-type data we show that the modeling error can be substantially reduced by about 18 % by incorporating field imperfections in both the transmit and receive coils.

[www] [BibTex]

Note: inproceedings, model-based

Abstract: To date a system matrix has to be obtained through a tedious calibration measurement when employing a systemmatrix-based reconstruction in magnetic particle imaging. This problem can be effectively addressed by model-based reconstruction, which takes into account both particle and scanner parameters. In this study, we focus onthe scanner parameters and in particular on the fact that the fields of experimental systems are imperfect. Forexperimental Lissajous-type data we show that the modeling error can be substantially reduced by about 18 % by incorporating field imperfections in both the transmit and receive coils.

[www]

Note: inproceedings, model-based

Abstract: To date a system matrix has to be obtained through a tedious calibration measurement when employing a systemmatrix-based reconstruction in magnetic particle imaging. This problem can be effectively addressed by model-based reconstruction, which takes into account both particle and scanner parameters. In this study, we focus onthe scanner parameters and in particular on the fact that the fields of experimental systems are imperfect. Forexperimental Lissajous-type data we show that the modeling error can be substantially reduced by about 18 % by incorporating field imperfections in both the transmit and receive coils.

[www]

Note: inproceedings, model-based

Abstract: To date a system matrix has to be obtained through a tedious calibration measurement when employing a systemmatrix-based reconstruction in magnetic particle imaging. This problem can be effectively addressed by model-based reconstruction, which takes into account both particle and scanner parameters. In this study, we focus onthe scanner parameters and in particular on the fact that the fields of experimental systems are imperfect. Forexperimental Lissajous-type data we show that the modeling error can be substantially reduced by about 18 % by incorporating field imperfections in both the transmit and receive coils.

[www] [BibTex]

Note: inproceedings, model-based

Abstract: To date a system matrix has to be obtained through a tedious calibration measurement when employing a systemmatrix-based reconstruction in magnetic particle imaging. This problem can be effectively addressed by model-based reconstruction, which takes into account both particle and scanner parameters. In this study, we focus onthe scanner parameters and in particular on the fact that the fields of experimental systems are imperfect. Forexperimental Lissajous-type data we show that the modeling error can be substantially reduced by about 18 % by incorporating field imperfections in both the transmit and receive coils.