Comparison of image quality metrics for electromagnetic wave propagation speed estimation in Breast Microwave Radar imaging scenarios
Bibliographic record
Abstract
Breast cancer is one of the most common causes of death amongst women. The earlier the cancer is treated, the better the chances for recovery. One of most promising complimentary imaging modalities for breast cancer detection is Breast Microwave Radar (BMR). The spatial accuracy of BMR images is dependent on the wave propagation speed estimate used to reconstruct the recorded breast structure responses. If an erroneous estimate is used, the resulting images will be spatially inaccurate and may contain artifacts, which can compromise the confidence of the diagnosis. In this paper we compare the fitness of four different image quality metrics (Contrast, Entropy, Tenengrad and Laplacian) when used for electromagnetic wave speed estimation for BMR imaging scenarios. The simulations were done varying the permittivity of the targets and the speed propagation of the wave in the medium. It demonstrated that the use of image quality metrics is a viable tool for BMR electromagnetic wave speed estimation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".