Evidence map›Paper›PMID 36616610›Full record

ArticleSensors (Basel, Switzerland)2022

A Novel Discretization Procedure in the CSI-FEM Algorithm for Brain Stroke Microwave Imaging.

Valeria Mariano, Jorge A Tobon Vasquez, Francesca Vipiana

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Valeria MarianoDepartment of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0003-1359-4912
Jorge A Tobon VasquezDepartment of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0003-4726-5017
Francesca VipianaDepartment of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0002-0791-9269

Funding

European Union's Horizon 2020 764479.
6 · The paper itself

Abstract

In this work, the contrast source inversion method is combined with a finite element method to solve microwave imaging problems. The paper's major contribution is the development of a novel contrast source variable discretization that leads to simplify the algorithm implementation and, at the same time, to improve the accuracy of the discretized quantities. Moreover, the imaging problem is recreated in a synthetic environment, where the antennas, and their corresponding coaxial port, are modeled. The implemented algorithm is applied to reconstruct the tissues' dielectric properties inside the head for brain stroke microwave imaging. The proposed implementation is compared with the standard one to evaluate the impact of the variables' discretization on the algorithm's accuracy. Furthermore, the paper shows the obtained performances with the proposed and the standard implementations of the contrast source inversion method in the same realistic 3D scenario. The exploited numerical example shows that the proposed discretization can reach a better focus on the stroke region in comparison with the standard one. However, the variation is within a limited range of permittivity values, which is reflected in similar averages.

Indexed as

Microwave ImagingStrokeAlgorithmsBrainHumansPhantoms, Imagingbrain strokecontrast source inversion methodfinite element methodmicrowave imaging

Identifiers

PMID36616610
PMCPMC9823425

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Registered trials

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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.