RBF Based Ultrasound Algorithm for Generation of Prior Information in MW Breast Imaging
Bibliographic record
Abstract
We present a new 3D quantitative ultrasound raybased inversion algorithm that uses radial basis functions (RBFs) to reconstruct ultrasonic properties from time-of-flight (TOF) and attenuation data. The algorithm extracts the TOF and attenuation data from measurements made on ultrasound signals transmitted between pairs of piezoelectric transducers positioned along the surface of a custom breast cup. The primary objective of this work is to generate informative ultrasonic property maps to be used as prior information for microwave breast imaging (MWI). Previous implementations relied on wholedomain polynomial basis functions, which produced inconsistent reconstructions that typically included artifacts. We address this by introducing RBFs to improve spatial resolution and accuracy through a framework capable of adaptive refinement. The framework allows multiple sets of RBFs that can be applied to distinct regions-of-interest within the imaging domain. Currently, region selection is performed using a data-driven, contrast-based approach, but the framework lays the foundation for future adaptive strategies, where resolution can be refined locally based on inversion performance and region-specific characteristics.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".