<title>Microwave detection of breast tumors: comparison of skin subtraction algorithms</title>
Bibliographic record
Abstract
Early detection of breast cancer is an important part of effective treatment. Microwave detection of breast cancer is of interest due to the contrast in dielectric properties of normal and malignant breast tissues. We are investigating a confocal microwave imaging system that adapts ideas from ground penetrating radar to breast cancer detection. In the proposed system, the patient lies prone with the breast extending through a hole in the examining table and encircled by an array of antennas. The breast is illuminated sequentially by each antenna with an ultrawideband signal, and the returns are recorded at the same antenna. Because the antennas are offset from the breast, the dominant component of the recorded returns is the reflection from the thin layer of breast skin. Two methods of reducing this reflection are compared, namely approximation of the signal with two time shifted, scaled and summed returns from a cylinder of skin, and subtraction of the mean of the set of aligned returns. Both approaches provide effective decrease of the skin signal, allowing for tumor detection.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".