Dual-energy imaging of the chest: Optimization of image acquisition techniques for the ‘bone-only’ image
Why this work is in the frame
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Bibliographic record
Abstract
Experiments were conducted to determine optimal acquisition techniques for bone image decompositions for a prototype dual-energy (DE) imaging system. Technique parameters included kVp pair (denoted [kVp(L)/kVp(H)]) and dose allocation (the proportion of dose in low- and high-energy projections), each optimized to provide maximum signal difference-to-noise ratio in DE images. Experiments involved a chest phantom representing an average patient size and containing simulated ribs and lung nodules. Low- and high-energy kVp were varied from 60-90 and 120-150 kVp, respectively. The optimal kVp pair was determined to be [60/130] kVp, with image quality showing a strong dependence on low-kVp selection. Optimal dose allocation was approximately 0.5-i.e., an equal dose imparted by the low- and high-energy projections. The results complement earlier studies of optimal DE soft-tissue image acquisition, with differences attributed to the specific imaging task. Together, the results help to guide the development and implementation of high-performance DE imaging systems, with applications including lung nodule detection and diagnosis, pneumothorax identification, and musculoskeletal imaging (e.g., discrimination of rib fractures from metastasis).
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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 | 0.000 |
| 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) | 0.000 | 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 it