Radar-based microwave imaging for breast cancer detection: tumor sensing with cross-polarized reflections
Bibliographic record
Abstract
Microwave imaging for breast cancer detection is based on the difference in electrical properties of normal, fatty breast tissues and tumors. Tumors may be detected by observing variations in microwave signals transmitted through or reflected from the breast. Radar-based breast imaging methods use the reflected signals from the breast to form images, and generally this involves co-polarized reflections. Observation of the cross-polarized reflection was proposed in S.C. Hagness et al. (IEEE Transac. Ant. Propag., pp. 783-791, 1999), and it was shown that the cross-polarized response did not contain reflections from planar interfaces such as the chest wall. In this paper, we further explore the application of cross-polarization to tumor detection. A broadband antenna capable of detecting cross-polarized reflections is simulated, constructed, and measured. The feasibility of tumor detection with cross-polarized reflections is examined through simulations and experimentally.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".