3D Quantitative Microwave Breast Imaging: Insights from Scans of Patients Undergoing Treatment
Bibliographic record
Abstract
Microwave imaging has recently attracted interest as a safe and comfortable method for breast imaging. Most previous experimental studies on breast imaging with microwave technology have used radar based approaches to produce qualitative images or two dimensional quantitative reconstructions. This paper presents a fast method for three-dimensional quantitative reconstruction of the breast using a planar high resolution transmission microwave system. In the previous work, we demonstrated the effectiveness of this approach using graphite phantoms and scans of healthy volunteers. In this study, results are presented for two breast cancer patients with different breast density categories prior to the initiation of chemotherapy. The 3D permittivity of both the healthy and cancerous breasts of these patients was reconstructed and compared with their mammograms. For the patient with extremely dense breast tissue, a significant difference was observed between the healthy and cancerous breast based on the permittivity images. Additionally, for one of the patients, the 3D permittivity of the cancerous breast was reconstructed both before and after chemotherapy. The results demonstrate that microwave imaging has the potential to effectively monitor changes in breast tissue during treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".