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Magnetic nanoparticle imaging by random and maximum length sequences of inhomogeneous activation fields

Baumgarten, D. and Eichardt, R. and Crevecoeur, G. and Supriyanto, E. and Haueisen, J. (2013) Magnetic nanoparticle imaging by random and maximum length sequences of inhomogeneous activation fields. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS.

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Official URL: https://www.ncbi.nlm.nih.gov/pubmed/24110423

Abstract

Biomedical applications of magnetic nanoparticles require a precise knowledge of their biodistribution. From multi-channel magnetorelaxometry measurements, this distribution can be determined by means of inverse methods. It was recently shown that the combination of sequential inhomogeneous excitation fields in these measurements is favorable regarding the reconstruction accuracy when compared to homogeneous activation . In this paper, approaches for the determination of activation sequences for these measurements are investigated. Therefor, consecutive activation of single coils, random activation patterns and families of m-sequences are examined in computer simulations involving a sample measurement setup and compared with respect to the relative condition number of the system matrix. We obtain that the values of this condition number decrease with larger number of measurement samples for all approaches. Random sequences and m-sequences reveal similar results with a significant reduction of the required number of samples. We conclude that the application of pseudo-random sequences for sequential activation in the magnetorelaxometry imaging of magnetic nanoparticles considerably reduces the number of required sequences while preserving the relevant measurement information.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Biomedical applications, magnetic nanoparticles, precise knowledge, biodistribution
Subjects:R Medicine > RS Pharmacy and materia medica
Divisions:Others
ID Code:51152
Deposited By: Haliza Zainal
Deposited On:27 Jan 2016 01:53
Last Modified:04 Sep 2017 14:39

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