Analysis of multilayer and single layer X-ray detectors for contrast-enhanced mammography using imaging task
Bibliographic record
Abstract
A multilayer (single-shot) detector has previously been proposed for contrast-enhanced mammography. The multilayer detector has the benefit of avoiding motion artifacts due to simultaneous acquisition of both high and low energy images. A single layer (dual-shot) detector has the benefit of better control over the energy separation since the incident beams can be produced and filtered separately. In this paper the performance of the multilayer detector is compared to that of a single layer detector using an ideal observer detectability index which is determined from an extended cascaded systems model and a defined imaging task. The detectors are assumed to have amorphous selenium direct conversion layers, however the same theoretical techniques used here may be applied to other types of integrating detectors. The anatomical noise caused by variation of glandularity within the breast is known to dominate the noise power spectrum at low frequencies due to its inverse power law dependence and is thus taken into account in our model to provide an accurate estimate of the detectability index. The conditions leading to the optimal detectability index, such as tube voltage, filtration, and weight factor are reported for both detector designs.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".