Differential Breast Microwave Radar Imaging: Diagnostic Performance Evaluation and Comparison to Single-Breast Diagnosis
Bibliographic record
Abstract
Microwave breast imaging (MBI) has been explored as a breast cancer diagnostic tool, but despite the proliferation of clinical evaluation of MBI systems, challenges remain before the modality is ready for clinical use. Suppression of the dominant skin responses, which obfuscate the interior tissues, is a major challenge. A possible solution to this challenge is differential imaging, rather than single-breast images, where only differences between the left/right breasts are displayed. This work presents the first estimates of diagnostic sensitivity and specificity obtained in MBI using a differential imaging approach. The delay-and-sum (DAS), delay-multiply-and-sum (DMAS), and optimization-based radar reconstruction (ORR) algorithms were used. Only the ORR method achieved better-than-random diagnostic performance when the tumour-detection criteria were defined using the signal-to-clutter ratio and localization error. This work also identified the potential of using the maximum image intensity as a diagnostic criterion. When this maximum-response-based metric was used, the diagnostic performance of all reconstruction methods improved. The ORR algorithm was the best performing method and achieved an area under the curve of the receiver operating characteristic curve of 84.6%.
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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 | 0.000 | 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".