Impact of Antenna Design on Image Quality in Breast Microwave Radar
Bibliographic record
Abstract
Limited access to breast cancer screening contributes to late-stage diagnoses in low-income and remote communities. Breast microwave sensing (BMS) systems provide a promising, cost-effective, and portable alternative to traditional screening methods. However, existing BMS systems vary substantially in design, equipment configuration, measurement protocols, and image reconstruction techniques. This work compares three common antenna types used in BMS systems-horn, Vivaldi, and flexible Printed Circuit Board (PCB)-to investigate how antenna design influences image quality. We evaluated spatial resolution, signal-to-noise ratio (SNR), signal-to-clutter ratio (SCR), and image accuracy using a standardized radar reconstruction method. Results show that the Vivaldi antenna achieved the best spatial resolution and highest SNR and SCR among the three despite having a lower gain and larger beamwidth than the horn antenna. These findings suggest that other antenna factors, such as crosssectional area, radiation pattern, and housing design, play an important role in microwave imaging beyond simply antenna gain, return loss and bandwidth. Understanding how these design parameters affect image quality is crucial for developing robust and accurate BMS systems, particularly for deployment in lowincome and remote regions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".