Analog receive signal processing for magnetic particle imaging

Graeser, Matthias; Knopp, Tobias; Grüttner, Mandy; Sattel, Timo F.; Buzug, Thorsten M.

doi:10.1118/1.4794482

Cited by 59 publications

(51 citation statements)

References 20 publications

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“…A total cancellation of the drive field feed‐through up to −125 dB was achieved (Table ). Eighth‐order band stop filters are theoretically able to suppress the drive field frequency band by up to 160 dB . Thus, the combined feed‐through suppression that is reported here is close to the damping by analog filters.…”

Section: Discussionsupporting

confidence: 65%

“…Additionally, the receive chain usually features a narrow band‐stop filter to cancel the direct drive field feed‐through that is orders of magnitudes higher than the particle signal. The feed‐through would render SPION detection impossible, due to the limited dynamic range of the analog‐to‐digital converter (ADC) as well as possible damage/saturation to the receive electronics …”

Section: Introductionmentioning

confidence: 99%

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Multifrequency magnetic particle imaging enabled by a combined passive and active drive field feed‐through compensation approach

et al. 2019

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PurposeMagnetic particle imaging (MPI) allows fast imaging of the spatial distribution of superparamagnetic iron‐oxide based nanoparticles (SPIONs). Recent research suggests that MPI furthermore promises in‐vivo access to environmental parameters of SPIONs as temperature or viscosity. Various medical applications as nanomedicine, stem cell‐based therapies or magnetic hyperthermia could benefit from in‐vivo multiparameter estimation by MPI. One possible approach to get access to functional parameters is particle excitation at multiple frequencies. To enable the investigation of the mentioned approach, a novel MPI device capable of multifrequency excitation is needed.MethodsMPI usually employs analog band‐stop filters to cancel the drive field feed‐through, which is magnitudes higher than the particle signal. To enable drive field frequency flexibility over a wide bandwidth, we propose a combined passive and active drive field feed‐through compensation approach. This cancellation technique further allows the direct detection of the SPIONs' signal at the fundamental excitation frequency.ResultsA combined feed‐through suppression of up to −125 dB is reported, which allows to adjust the drive field frequency from 500 Hz to 20 kHz. Initial spectroscopic measurements and images are shown that demonstrate the concept of multifrequency excitation and prove the imaging capability of the presented scanner. A mean signal‐to‐noise ratio (SNR) enhancement by the factor of 1.7 was shown when the first harmonic is used for measurement‐based image reconstruction compared to when it is omitted.ConclusionsIn this paper, the first one‐dimensional multifrequency magnetic particle imaging (mf‐MPI) that features adjustable excitation frequencies from 500 Hz to 20 kHz is presented. The device will be used to study the principle of multiparameter estimation by employing multifrequency excitation.

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Section: Discussionsupporting

confidence: 65%

Section: Introductionmentioning

confidence: 99%

Multifrequency magnetic particle imaging enabled by a combined passive and active drive field feed‐through compensation approach

et al. 2019

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“…As pointed out by Graeser et al [10], when using the cancellation technique with a gradiometer, it is essential that the cancellation signal received by the gradiometer coil has the same phase and amplitude as the induced excitation signal.…”

Section: Discussionmentioning

confidence: 99%

“…We developed a simple and practical me-thod for correcting the inhomogeneous sensitivity of a receiving coil together with the feed through interference using a blank scan [9]. By combining the filtering method adopted by Graeser et al [10] and our method [9], we would expect that the reliability of our MPI system can be further enhanced. In this study, we investigated the effect of signal filtering with various analog filter modes on the image quality and quantitativity of the MPI images obtained by our projection-based MPI system using phantom studies.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Signal Filtering on Image Quality of Projection-Based Magnetic Particle Imaging

Shimada¹,

Murase²

2017

OJMI

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Purpose: Magnetic particle imaging (MPI) allows for imaging of the spatial distribution of magnetic nanoparticles (MNPs) in positive contrast, with high sensitivity, high spatial resolution, and high imaging speed. It is necessary to increase the signal-to-noise ratio to enhance the reliability of MPI. The purpose of this study was to investigate the effect of signal filtering on the image quality and quantitativity in projection-based MPI using phantoms. Materials and Methods: We fabricated two kinds of phantom (cylindrical tube phantom with a diameter of 6 mm and A-shaped phantom) and evaluated the effect of signal filtering in terms of root-mean-square (RMS) granularity and the correlation coefficient between iron concentrations of MNPs and average MPI values for four filter modes (THRU, BPF, BEF, and LPF). In the THRU mode, the signal input was output without passing through the filter. In the BPF mode, only the third-harmonic signal was passed using a band-pass filter (central frequency: 1200 Hz, band width: 1/3 octave). In the BEF mode, the first-harmonic signal was eliminated using a band-elimination filter (central frequency: 400 Hz, band width: 1/3 octave). In the LPF mode, only the signal with a frequency less than the third-harmonic frequency was passed using a low-pass filter (cut-off frequency: 1200 Hz, −24 ± 2 dB/octave). The RMS granularity was obtained by calculating standard deviations of the pixel values in the MPI image without MNPs, whereas average MPI values were obtained by drawing a circular region of interest with a diameter of 6 mm on the MPI image of the cylindrical tube phantom. Results: When using the filtered backprojection (FBP) method with a ramp filter for image reconstruction, the RMS granularity and correlation coefficient decreased in the order of THRU, BPF, BEF, and LPF. In the BPF mode, however, some artifacts were observed. When using the maximum likelihood-expectation maximization (ML-EM) algorithm with an iteration number of 15, the correlation coefficient decreased in the order of THRU, BPF, BEF, and LPF, whereas the RMS granularity did not largely depend on the filter mode and was significantly (p < 0.05) lower than that for the FBP method for all the filter modes. Conclusion: The BEF mode is adequate for the FBP method in projection-based MPI, whereas THRU is a best option in use of the ML-EM algorithm.

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Magnetic Particle Imaging

Zheng

Konkle³

et al. 2016

Design and Applications of Nanoparticles in Biomedical Imaging

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Analog receive signal processing for magnetic particle imaging

Abstract: By recovering the full particle signal the SNR can be improved and errors in the x-space reconstruction are prevented. The authors show that the combined method provides this full particle signal and makes it possible to improve image quality.

Cited by 59 publications

References 20 publications

Multifrequency magnetic particle imaging enabled by a combined passive and active drive field feed‐through compensation approach

Multifrequency magnetic particle imaging enabled by a combined passive and active drive field feed‐through compensation approach

Effect of Signal Filtering on Image Quality of Projection-Based Magnetic Particle Imaging

Magnetic Particle Imaging

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