Evidence map›Paper›PMID 40431965›Full record

ArticleSensors (Basel, Switzerland)2025

Non-Uniform Antenna Array for Enhanced Medical Microwave Imaging.

Younis M Abbosh, Kamel Sultan, Lei Guo, Amin Abbosh

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Younis M AbboshCollege of Electronics Engineering, Ninevah University, Mosul 41002, Iraq.ORCID 0000-0002-0494-7926
Kamel SultanSchool of EECS, The University of Queensland, St. Lucia, QLD 4072, Australia.ORCID 0000-0003-2756-4765
Lei GuoSchool of EECS, The University of Queensland, St. Lucia, QLD 4072, Australia.ORCID 0000-0003-4340-5801
Amin AbboshSchool of EECS, The University of Queensland, St. Lucia, QLD 4072, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A non-uniform antenna array is proposed to enhance the accuracy of medical microwave imaging systems by increasing the amount of useful information captured about the imaged domain without increasing the number of antennas. These systems have so far been using uniform antenna arrays, which lead to highly correlated signals, limiting the amount of imaging information and adversely affecting diagnostic accuracy. In the proposed non-uniform antenna array method, the optimal number and positions of antennas are calculated with the aim of enhancing spatial diversity and reducing information redundancy. The mutual information coefficient is used as a metric to evaluate and minimize redundancy between received signals. A microwave head imaging system is used to verify the proposed approach. The results of the investigated scenarios show that using a non-uniform antenna configuration outperforms a uniform setup in imaging accuracy and clarity, when using the same number of antennas. Moreover, the reconstructed images demonstrate that using an optimized non-uniform antenna array with fewer elements can outperform a uniform array with more elements in terms of localization accuracy and image quality. The proposed approach improves imaging performance and reduces system complexity, cost, and power consumption, making it a practical solution for real-world biomedical imaging applications.

Indexed as

Diagnostic ImagingMicrowave ImagingMicrowavesAlgorithmsHeadHumansImage Processing, Computer-Assistedconfocal imagingelectromagnetic imagingmedical microwave imagingnon-uniform antenna array

Identifiers

PMID40431965
PMCPMC12116185

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.