Spectral Difference Between Microwave Radar and Microwave-Induced Thermoacoustic Signals
Bibliographic record
Abstract
This letter presents a spectral content comparison of the signals generated in the microwave radar (MR) and microwave-induced thermoacoustic (MIT) imaging systems. Two physical processes occur when microwave interacts with a lossy dielectric object. First, due to the contrast in the complex permittivity between the embedded object and background medium, reflection of microwave energy occurs at the interface. Second, due to the contrast in the absorption coefficient between the object and background medium and the consequent thermal expansion, microwave induces an acoustic wave. As a method of comparison between the inputs and outputs of the MR and MIT processes, we define the MR and MIT channels. We use a two-dimensional (2-D) example to demonstrate that the MR channel over the ultrawideband (UWB) spectrum from 3.1 to 10.6 GHz manifests different fading from the MIT channel over the ultrasonic spectrum from 0.32 to 1.10 MHz. The two output signals are distinctive, but they are co-registered to the same object. Hence, using the information provided by both could enhance the imaging modality. We apply this dual-physics scheme in the context of breast 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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".