Evidence map›Paper›PMID 35161640›Full record

ArticleSensors (Basel, Switzerland)2022

Adaptive Model for Magnetic Particle Mapping Using Magnetoelectric Sensors.

Ron-Marco Friedrich, Franz Faupel

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ron-Marco FriedrichInstitute of Materials Science, Faculty of Engineering, Kiel University, 24143 Kiel, Germany.ORCID 0000-0003-3584-1611
Franz FaupelInstitute of Materials Science, Faculty of Engineering, Kiel University, 24143 Kiel, Germany.ORCID 0000-0003-3367-1655

Funding

Deutsche Forschungsgemeinschaft CRC1261 Project B7
6 · The paper itself

Abstract

Imaging of magnetic nanoparticles (MNPs) is of great interest in the medical sciences. By using resonant magnetoelectric sensors, higher harmonic excitations of MNPs can be measured and mapped in space. The proper reconstruction of particle distribution via solving the inverse problem is paramount for any imaging technique. For this, the forward model needs to be modeled accurately. However, depending on the state of the magnetoelectric sensors, the projection axis for the magnetic field may vary and may not be known accurately beforehand. As a result, the projection axis used in the model may be inaccurate, which can result in inaccurate reconstructions and artifact formation. Here, we show an approach for mapping MNPs that includes sources of uncertainty to both select the correct particle distribution and the correct model simultaneously.

Indexed as

Magnetite NanoparticlesDiagnostic ImagingMagnetic FieldsMagneticsMagnetite Nanoparticlesblind deconvolutionimaginginverse problemmagnetic nanoparticlemagnetoelectric

Identifiers

PMID35161640
PMCPMC8839579

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.