Spatial Resolution Evaluation of a Microwave System for Breast Cancer Screening
Bibliographic record
Abstract
The ability of microwave breast imaging to achieve sub-centimeter spatial resolution has been proven before in simulation and simple experimental studies. However, detecting sub-centimeter tumours depends not only on the theoretical spatial resolution limit, but also on the level of background clutter and measurement uncertainty. Therefore, estimating the actual limit of the smallest detectable object in a specific measurement setup is critical before the setup can be deployed in a clinical scenario. Here, we present a method of such evaluation on a planar microwave imaging setup for breast cancer imaging. The method utilizes the measurement of a small scattering probe of known size and permittivity in a uniform embedding medium. The contrast-to-noise ratio (CNR) of the generated point spread function can then be evaluated to determine the system-specific spatial resolution. The effectiveness of this approach is demonstrated in an experimental study of a compressed-breast phantom. This method can be applied to evaluate the limit of the size of detectable objects for other acquisitions systems, e.g. hemispherical or cylindrical antenna configurations.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| 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".