Design of a fast-shaping amplifier for PET/CT APD detectors with depth-of-interaction
Bibliographic record
Abstract
An integrated 0.35-/spl mu/m CMOS fast-shaping amplifier has been designed for coincidence detection and zero-cross time pulse-shape discrimination (PSD) in positron emission tomography (PET) and for high-rate event counting in computerized tomography (CT) with avalanche photodiode (APD)-based detectors. Analytical simulations of CR-RC/sup n/ filters of various order and shaping time constant were carried out to optimize the timing performance, keeping in mind the stringent channel density requirements of the detector front-end electronics. The filter was implemented with the biquadratic bandpass architecture using a folded cascode transconductance amplifier. The electronic timing resolution of the coincidence circuit was 92 ps in the ideal case without an APD (C/sub in/ = 0 pF), and 243 ps with an APD (C/sub in/ = 30 pF). By comparison, the same system with the CMOS shaper replaced by an Ortec 579 Fast Filter Amplifier set to a shaping time of 10 ns yielded an electronic time resolution of 79 ps in the ideal case without capacitance and 236 ps with the APD. The 511-keV coincidence time resolution for a crystal scintillator-based lutetium oxyorthosilicate (LSO)-APD detector was measured to be 1.49 ns.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".