Comparison of Threshold Energy Calibrations of a Photon-Counting Detector and Impact on CT Reconstruction
Bibliographic record
Abstract
Photon-counting detectors (PCDs) require a more complicated calibration process than the standard energy-integrating detectors. The first step of a PCD calibration is the threshold energy calibration. This step determines the linear pixel-by-pixel relationship between the output voltage of a PCD and the incoming photon energy. It can be performed in several ways. Three different methods were implemented, requiring only a standard X-ray source, or an X-ray source combined with K-edge materials or a PCD response model. The three resulting calibrations were first evaluated on monoenergetic and projection measurements. The impact of the threshold calibration on computed tomography (CT) images was also studied. The calibration method fitting a detector response model to polyenergetic measurements presented the best spectral accuracy when estimating monoenergetic peaks. This calibration also produced a better pixel homogeneity in an air projection. However, no significant improvement was observed in the noise power spectrum (NPS) and ring artifact evaluation of a conventional CT image for this calibration compared to a calibration providing lower spectral accuracy or lower pixel homogeneity.
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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 | 0.000 |
| 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 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".