High Rate Photon Counting CT Using Parallel Digital PET Electronics
Bibliographic record
Abstract
Recent developments in detectors and electronics enable both positron emission tomography (PET) and X-ray computed tomography (CT) data to be acquired concurrently using the same detection front-end for dual-modality PET/CT imaging. Moreover, it would potentially allow substantial reduction of cost and housing size, in addition to facilitating image fusion. However, the lower energy signals ( ~60 keV versus 511 keV) and higher photon flux per pixel ( > 1 Mcps versus 10 kcps) in CT relative to PET cause significant pile-up and dead-time in CT data acquired in photon counting mode. A digital signal processing method was developed and implemented to improve processing of detector signals sampled at low frequency (~ 45 MHz) in presence of pile-up. The method consists in digitally subtracting the detector impulse response at the output of the preamplifier to restore the signal baseline for more accurate energy estimation. When compared to a fixed threshold counting technique, the proposed method features better noise immunity, higher energy resolution and 50% higher rates measured at an estimated true rate of 2.75 Mcps, making CT integration within modern digital PET hardware feasible.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".