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Weighted iterative reconstruction for magnetic particle imaging

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Weighted iterative reconstruction for magnetic particle imaging. / Knopp, T; Rahmer, J; Sattel, T F; Biederer, S; Weizenecker, J; Gleich, B; Borgert, J; Buzug, T M.

In: PHYS MED BIOL, Vol. 55, No. 6, 21.03.2010, p. 1577-89.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Knopp, T, Rahmer, J, Sattel, TF, Biederer, S, Weizenecker, J, Gleich, B, Borgert, J & Buzug, TM 2010, 'Weighted iterative reconstruction for magnetic particle imaging', PHYS MED BIOL, vol. 55, no. 6, pp. 1577-89. https://doi.org/10.1088/0031-9155/55/6/003

APA

Knopp, T., Rahmer, J., Sattel, T. F., Biederer, S., Weizenecker, J., Gleich, B., Borgert, J., & Buzug, T. M. (2010). Weighted iterative reconstruction for magnetic particle imaging. PHYS MED BIOL, 55(6), 1577-89. https://doi.org/10.1088/0031-9155/55/6/003

Vancouver

Knopp T, Rahmer J, Sattel TF, Biederer S, Weizenecker J, Gleich B et al. Weighted iterative reconstruction for magnetic particle imaging. PHYS MED BIOL. 2010 Mar 21;55(6):1577-89. https://doi.org/10.1088/0031-9155/55/6/003

Bibtex

@article{e63bfb22e81f458f8ed55c4bda822073,
title = "Weighted iterative reconstruction for magnetic particle imaging",
abstract = "Magnetic particle imaging (MPI) is a new imaging technique capable of imaging the distribution of superparamagnetic particles at high spatial and temporal resolution. For the reconstruction of the particle distribution, a system of linear equations has to be solved. The mathematical solution to this linear system can be obtained using a least-squares approach. In this paper, it is shown that the quality of the least-squares solution can be improved by incorporating a weighting matrix using the reciprocal of the matrix-row energy as weights. A further benefit of this weighting is that iterative algorithms, such as the conjugate gradient method, converge rapidly yielding the same image quality as obtained by singular value decomposition in only a few iterations. Thus, the weighting strategy in combination with the conjugate gradient method improves the image quality and substantially shortens the reconstruction time. The performance of weighting strategy and reconstruction algorithms is assessed with experimental data of a 2D MPI scanner.",
keywords = "Algorithms, Image Enhancement, Least-Squares Analysis, Magnetics, Metal Nanoparticles, Molecular Imaging, Particle Size, Sensitivity and Specificity, Time Factors, Journal Article",
author = "T Knopp and J Rahmer and Sattel, {T F} and S Biederer and J Weizenecker and B Gleich and J Borgert and Buzug, {T M}",
year = "2010",
month = mar,
day = "21",
doi = "10.1088/0031-9155/55/6/003",
language = "English",
volume = "55",
pages = "1577--89",
journal = "PHYS MED BIOL",
issn = "0031-9155",
publisher = "IOP Publishing Ltd.",
number = "6",

}

RIS

TY - JOUR

T1 - Weighted iterative reconstruction for magnetic particle imaging

AU - Knopp, T

AU - Rahmer, J

AU - Sattel, T F

AU - Biederer, S

AU - Weizenecker, J

AU - Gleich, B

AU - Borgert, J

AU - Buzug, T M

PY - 2010/3/21

Y1 - 2010/3/21

N2 - Magnetic particle imaging (MPI) is a new imaging technique capable of imaging the distribution of superparamagnetic particles at high spatial and temporal resolution. For the reconstruction of the particle distribution, a system of linear equations has to be solved. The mathematical solution to this linear system can be obtained using a least-squares approach. In this paper, it is shown that the quality of the least-squares solution can be improved by incorporating a weighting matrix using the reciprocal of the matrix-row energy as weights. A further benefit of this weighting is that iterative algorithms, such as the conjugate gradient method, converge rapidly yielding the same image quality as obtained by singular value decomposition in only a few iterations. Thus, the weighting strategy in combination with the conjugate gradient method improves the image quality and substantially shortens the reconstruction time. The performance of weighting strategy and reconstruction algorithms is assessed with experimental data of a 2D MPI scanner.

AB - Magnetic particle imaging (MPI) is a new imaging technique capable of imaging the distribution of superparamagnetic particles at high spatial and temporal resolution. For the reconstruction of the particle distribution, a system of linear equations has to be solved. The mathematical solution to this linear system can be obtained using a least-squares approach. In this paper, it is shown that the quality of the least-squares solution can be improved by incorporating a weighting matrix using the reciprocal of the matrix-row energy as weights. A further benefit of this weighting is that iterative algorithms, such as the conjugate gradient method, converge rapidly yielding the same image quality as obtained by singular value decomposition in only a few iterations. Thus, the weighting strategy in combination with the conjugate gradient method improves the image quality and substantially shortens the reconstruction time. The performance of weighting strategy and reconstruction algorithms is assessed with experimental data of a 2D MPI scanner.

KW - Algorithms

KW - Image Enhancement

KW - Least-Squares Analysis

KW - Magnetics

KW - Metal Nanoparticles

KW - Molecular Imaging

KW - Particle Size

KW - Sensitivity and Specificity

KW - Time Factors

KW - Journal Article

U2 - 10.1088/0031-9155/55/6/003

DO - 10.1088/0031-9155/55/6/003

M3 - SCORING: Journal article

C2 - 20164532

VL - 55

SP - 1577

EP - 1589

JO - PHYS MED BIOL

JF - PHYS MED BIOL

SN - 0031-9155

IS - 6

ER -