Analytic pulse height correction in dual-ended readout PET detectors
Bibliographic record
Abstract
We propose an analytical method for pulse height correction to enable a global energy spectrum and to restore uniformity of signal asymmetry used for extraction of depth of interaction (DOI) information in PET detectors with dual-ended readout configuration. The method is based on empirically modifying the pulse heights obtained from two ends of crystals to correct for non-linear dependency of light output on DOI before calculating energy or DOI. Experiments with saw-cut, high aspect ratio crystals (1×1×20 mm3LYSO) showed that an improvement in global energy resolution from 48% to 18% is obtained using our method without any calibration of the energy spectrum based on DOI. We also observed improvement in uniformity of signal asymmetry along the crystal by correcting pulse heights using the proposed method. Details of correction method, its effect on energy resolution and signal asymmetry and/or DOI profile, as well as results of optimization of the method based on maximizing the peak-to-valley ratio of the photopeak are presented and discussed. The proposed method finds application in calibration and signal processing of DOI PET detectors based on dual-ended readout configuration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".