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Record W4394744459 · doi:10.1109/jerm.2024.3385335

Surface Wave and Back Radiation Suppression in Microwave Breast Screening

2024· article· en· W4394744459 on OpenAlexafffund
Milad Mokhtari, Milica Popović

Bibliographic record

VenueIEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology · 2024
Typearticle
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrowaveRadiationSurface wavePhysicsAcousticsOpticsMedical physicsMedicineTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

The challenges in antenna design for microwave-based breast screening systems identify two distinct needs: 1) to minimize the surface-wave propagation at the interface between the substrate and the tissue, and 2) to address the back-radiation. These surface waves become more noticeable within the substrate, particularly when a confining ground plane is present, and yet the ground plane is pivotal for achieving unidirectionality and shielding against environmental radiation. This paper introduces a simplified human breast model and offers a quantitative analysis of existing surface waves. We then propose a 16-antenna array of cavity-backed patch antennas with parasitic elements, designed for operation in the 3.1–5.1 GHz range. Each antenna element is optimized to function seamlessly alongside the breast tissue. Full-wave simulations illustrate that the proposed antenna array achieves superior unidirectionality and diminished mutual coupling levels when compared to its predecessor. We further outline the cost-effective fabrication method that employs the SYLGARD(TM) 184 silicone elastomer PDMS kit. The measurements from the fabricated antenna elements are consistent with the results of the full-wave simulations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.304
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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