A Monolithic Amorphous-Selenium/CMOS Small-Pixel-Effect-Enhanced X-Ray-Energy-Discriminating Quantum-Counting Pixel for Biomedical Imaging
Bibliographic record
Abstract
We demonstrate the first dual-energy-discriminating quantum-counting-detector (ED-QCD) pixel with an amorphous X-ray-sensitive semiconductor, amorphous selenium (a-Se), monolithically integrated with a custom CMOS readout IC (ROIC). Our $92\times 92\mu \mathrm{m}^{2}$ large-area scalable pixel is also the first to exploit the small pixel effect (SPE) in amorphous semiconductors for dual-X-ray-energy quantum counting. SPE enables 7.9keV energy resolution and $35\mathrm{Mcps}/\mathrm{mm}^{2}$ count rate density that can satisfy even demanding medical-imaging applications like dedicated breast computed tomography (DBCT). Our novel pixel architecture achieves the design objectives by leveraging (1) area-efficient SPE-enhanced sub-pixels with shared counters, and (2) a partially-shared foreground input-offset-correction circuit employing a (3) new area-efficient current-steering calibration DAC.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".