Detection and Compensation of Periodic Motion in Magnetic Particle Imaging

TY - JOUR

T1 - Detection and Compensation of Periodic Motion in Magnetic Particle Imaging

AU - Gdaniec, Nadine

AU - Schluter, Matthias

AU - Möddel, Martin

AU - Kaul, Michael

AU - Krishnan, Kannan

AU - Schlafer, Alexander

AU - Knopp, Tobias

PY - 2017/7

Y1 - 2017/7

N2 - The temporal resolution of the tomographic imaging method magnetic particle imaging (MPI) is remarkably high. The spatial resolution is degraded for measured voltage signal with low signal-to-noise ratio, because the regularization in the image reconstruction step needs to be increased for system-matrix approaches and for deconvolution steps in x-space approaches. To improve the signal-to-noise ratio, block-wise averaging of the signal over time can be advantageous. However, since block-wise averaging decreases the temporal resolution, it prevents resolving the motion. In this work, a framework for averaging motioncorrupted MPI raw data is proposed. The motion is considered to be periodic as it is the case for respiration and/or the heart beat. The same state of motion is thus reached repeatedly in a time series exceeding the repetition time of the motion and can be used for averaging. As the motion process and the acquisition process are in general not synchronized, averaging of the captured MPI raw data corresponding to the same state of motion requires to shift the starting point of the individual frames. For highfrequency motion, a higher frame rate is potentially required. To address this issue, a binning method for using only parts of complete frames from a motion cycle is proposed that further reduces the motion artifacts in the final images. The frequency of motion is derived directly from the MPI raw data signal without the need to capture an additional navigator signal. Using a motion phantom it is shown that the proposed method is capable of averaging experimental data with reduced motion artifacts. The methods are further validated on in-vivo data from mouse experiments to compensate the heart beat.

AB - The temporal resolution of the tomographic imaging method magnetic particle imaging (MPI) is remarkably high. The spatial resolution is degraded for measured voltage signal with low signal-to-noise ratio, because the regularization in the image reconstruction step needs to be increased for system-matrix approaches and for deconvolution steps in x-space approaches. To improve the signal-to-noise ratio, block-wise averaging of the signal over time can be advantageous. However, since block-wise averaging decreases the temporal resolution, it prevents resolving the motion. In this work, a framework for averaging motioncorrupted MPI raw data is proposed. The motion is considered to be periodic as it is the case for respiration and/or the heart beat. The same state of motion is thus reached repeatedly in a time series exceeding the repetition time of the motion and can be used for averaging. As the motion process and the acquisition process are in general not synchronized, averaging of the captured MPI raw data corresponding to the same state of motion requires to shift the starting point of the individual frames. For highfrequency motion, a higher frame rate is potentially required. To address this issue, a binning method for using only parts of complete frames from a motion cycle is proposed that further reduces the motion artifacts in the final images. The frequency of motion is derived directly from the MPI raw data signal without the need to capture an additional navigator signal. Using a motion phantom it is shown that the proposed method is capable of averaging experimental data with reduced motion artifacts. The methods are further validated on in-vivo data from mouse experiments to compensate the heart beat.

KW - Journal Article

U2 - 10.1109/TMI.2017.2666740

DO - 10.1109/TMI.2017.2666740

M3 - SCORING: Journal article

C2 - 28207386

VL - 36

SP - 1511

EP - 1521

JO - IEEE T MED IMAGING

JF - IEEE T MED IMAGING

SN - 0278-0062

IS - 7

ER -